Standard cytogenetic techniques (chromosomal banding analysis-CBA, and fluorescence in situ hybridization-FISH) show limits in characterizing complex chromosomal rearrangements and structural variants arising from two or more chromosomal breaks. In this study, we applied optical genome mapping (OGM) to fully characterize two cases of complex chromosomal rearrangements at high resolution. In case 1, an acute myeloid leukemia (AML) patient showing chromothripsis, OGM analysis was fully concordant with classic cytogenetic techniques and helped to better refine chromosomal breakpoints. The OGM results of case 2, a patient with non-Hodgkin lymphoma, were only partially in agreement with previous cytogenetic analyses and helped to better define clonal heterogeneity, overcoming the bias related to clonal selection due to cell culture of cytogenetic techniques. In both cases, OGM analysis led to the identification of molecular markers, helping to define the pathogenesis, classification, and prognosis of the analyzed patients. Despite extensive efforts to study hematologic diseases, standard cytogenetic methods display unsurmountable limits, while OGM is a tool that has the power to overcome these limitations and provide a cytogenetic analysis at higher resolution. As OGM also shows limits in defining regions of a repetitive nature, combining OGM with CBA to obtain a complete cytogenetic characterization would be desirable.

Optical genome mapping (OGM) is a technique that extracts partial genomic information from optically imaged and linearized DNA fragments containing fluorescently labeled short sequence patterns. This information can be used for various genomic analyses and applications, such as the detection of structural variations and copy-number variations, epigenomic profiling, and microbial species identification. Currently, the choice of labeled patterns is based on the available biochemical methods and is not necessarily optimized for the application.
In this work, we develop a model of OGM based on information theory, which enables the design of optimal labeling patterns for specific applications and target organism genomes. We validated the model through experimental OGM on human DNA and simulations on bacterial DNA. Our model predicts up to 10-fold improved accuracy by optimal choice of labeling patterns, which may guide future development of OGM biochemical labeling methods and significantly improve its accuracy and yield for applications such as epigenomic profiling and cultivation-free pathogen identification in clinical samples.
https://github.com/yevgenin/PatternCode.

Optical mapping-a technique that visualizes short sequence motives along DNA molecules of hundred kilobases to megabase in size-has found an important place in genome research. It is widely used to facilitate genome sequence assemblies and analyses of genome structural variations. Application of the technique is conditional on availability of highly pure ultra-long high-molecular-weight DNA (uHMW DNA), which is challenging to achieve in plants due to the presence of the cell wall, chloroplasts, and secondary metabolites, just as a high content of polysaccharides and DNA nucleases in some species. These obstacles can be overcome by employment of flow cytometry, enabling a fast and highly efficient purification of cell nuclei or metaphase chromosomes, which are afterward embedded in agarose plugs and used to isolate the uHMW DNA in situ. Here, we provide a detailed protocol for the flow sorting-assisted uHMW DNA preparation that has been successfully used to construct whole-genome as well as chromosomal optical maps for 20 plant species from several plant families.

(1) Background: Optical genome mapping (OGM) is a novel approach to identifying genomic structural variations with high accuracy and resolution. We report a proband with severe short stature caused by 46, XY, der (16) ins (16;15) (q23; q21.3q14) that was detected by OGM combined with other tests and review the clinical features of patients with duplication within 15q14q21.3; (2) Methods: OGM, whole exon sequencing (WES), copy number variation sequencing (CNV-seq), and karyotyping were used; (3) Results: The proband was a 10.7-year-old boy with a complaint of severe short stature (-3.41SDS) and abnormal gait. He had growth hormone deficiency, lumbar lordosis, and epiphyseal dysplasia of both femurs. WES and CNV-seq showed a 17.27 Mb duplication of chromosome 15, and there was an insertion in chromosome 16 found by karyotyping. Furthermore, OGM revealed that duplication of 15q14q21.3 was inversely inserted into 16q23.1, resulting in two fusion genes. A total of fourteen patients carried the duplication of 15q14q21.3, with thirteen previously reported and one from our center, 42.9% of which were de novo. In addition, neurologic symptoms (71.4%,10/14) were the most common phenotypes; (4) Conclusions: OGM combined with other genetic methods can reveal the genetic etiology of patients with the clinical syndrome, presenting great potential for use in properly diagnosing in the genetic cause of the clinical syndrome.

Much of the human genetics variant repertoire is composed of single nucleotide variants (SNV) and small insertion/deletions (indel) but structural variants (SV) remain a major part of our modified DNA. SV detection has often been a complex question to answer either because of the necessity to use different technologies (array CGH, SNP array, Karyotype, Optical Genome Mapping…) to detect each category of SV or to get an appropriate resolution (Whole Genome Sequencing). Thanks to the deluge of pangenomic analysis, Human geneticists are accumulating SV and their interpretation remains time consuming and challenging. The AnnotSV webserver (https://www.lbgi.fr/AnnotSV/) aims at being an efficient tool to (i) annotate and interpret SV potential pathogenicity in the context of human diseases, (ii) recognize potential false positive variants from all the SV identified and (iii) visualize the patient variants repertoire. The most recent developments in the AnnotSV webserver are: (i) updated annotations sources and ranking, (ii) three novel output formats to allow diverse utilization (analysis, pipelines), as well as (iii) two novel user interfaces including an interactive circos view.

Efficient tapping into genomic information from a single microscopic image of an intact DNA molecule is an outstanding challenge and its solution will open new frontiers in molecular diagnostics. Here, a new computational method for optical genome mapping utilizing deep learning is presented, termed DeepOM. Utilization of a convolutional neural network, trained on simulated images of labeled DNA molecules, improves the success rate in the alignment of DNA images to genomic references.
The method is evaluated on acquired images of human DNA molecules stretched in nano-channels. The accuracy of the method is benchmarked against state-of-the-art commercial software Bionano Solve. The results show a significant advantage in alignment success rate for molecules shorter than 50 kb. DeepOM improves the yield, sensitivity, and throughput of optical genome mapping experiments in applications of human genomics and microbiology.
The source code for the presented method is publicly available at https://github.com/yevgenin/DeepOM.

BACKGROUND: With stage 5 chronic kidney disease (CKD5) more prevalent in the Czech Republic than in most European countries, genetic susceptibility is potentially implicated.
METHODS: In a group of 1489 CKD5 kidney transplantation patients (93% with complete clinical characteristics; mean age 52.0 years, 37% females) and 2559 healthy controls (mean age 49.0 years, 51% females), we examined the prevalence of six APOL1 SNPs (rs73885319, rs71785313, rs13056427, rs136147, rs10854688 and rs9610473) and one newly detected 55-nucleotide insertion/deletion polymorphism.
RESULTS: The rs73885319 and rs71785313 variants were monomorphic in the Czech Caucasian population. Genotype frequencies of the three SNPs examined (rs13056427, rs136147 and rs9610473) were almost identical in patients and controls (all P values were between 0.39 and 0.91). Minor homozygotes of rs10854688 were more common between the patients (13.2%) than in controls (10.7%) (OR [95% CI]; 1.32 [1.08-1.64]; P < 0.01). Prevalence of the newly detected 55-bp APOL1 deletion was significantly higher in CKD5 patients (3.0% vs. 1.7%; OR [95% CI]; 1.80 [1.16-2.80]; P < 0.01) compared to controls. Frequencies of some individual APOL1 haplotypes were borderline different between patients and controls.
CONCLUSIONS: We found an association between rs10854688 SNP within the APOL1 gene and end-stage renal disease in the Czech Caucasian population. Further independent studies are required before a conclusive association between the newly detected APOL1 insertion/deletion polymorphism and CKD5 can be confirmed.

Optical mapping plays an important role in plant genomics, particularly in plant genome assembly and large-scale structural variation detection. While DNA sequencing provides base-by-base nucleotide information, optical mapping shows the physical locations of selected enzyme restriction sites in a genome. The long single-molecule maps produced by optical mapping make it a useful auxiliary technique to DNA sequencing, which generally cannot span large and complex genomic regions. Although optical mapping, therefore, offers unique advantages to researchers, there are few dedicated tools to assist in optical mapping analyses. In this chapter, we present runBNG2, a successor of runBNG to help optical-mapping data analysis for diverse datasets.

BACKGROUND: The PX330 and the related PX459 plasmids are widely used for Clustered Regularly Interspaced Short Palindromic Repeat (CRISPR)/Cas9-mediated genome editing. Screening for plasmids containing the correct sgRNA template insertion is one of the most important steps in this system. Different methods for screening the sgRNA inserts have been deployed. One such method is Restriction Enzyme (RE) mapping. Restriction enzyme mapping can be used to screen for numerous plasmid recombinants simultaneously.
METHODS: In this study, the sgRNA templates were initially cloned into the above PX459 plasmids. Subsequently, the accuracy of the constructs was determined by RE mapping.
RESULTS: This method was established to screen for sgRNA-bearing PX459 plasmids. However, numerous anomalies were detected after ligation of sgRNA templates into RE digested PX459 plasmids.
CONCLUSIONS: Our data suggest that RE mapping is only appropriate as an initial screen and that the identity of all plasmids with the correctly identified RE maps should be confirmed by Sanger sequencing.

BACKGROUND: Optical maps record locations of specific enzyme recognition sites within long genome fragments. This long-distance information enables aligning genome assembly contigs onto optical maps and ordering contigs into scaffolds. The generated scaffolds, however, often contain a large amount of gaps. To fill these gaps, a feasible way is to search genome assembly graph for the best-matching contig paths that connect boundary contigs of gaps. The combination of searching and evaluation procedures might be \"searching followed by evaluation\", which is infeasible for long gaps, or \"searching by evaluation\", which heavily relies on heuristics and thus usually yields unreliable contig paths.
RESULTS: We here report an accurate and efficient approach to filling gaps of genome scaffolds with aids of optical maps. Using simulated data from 12 species and real data from 3 species, we demonstrate the successful application of our approach in gap filling with improved accuracy and completeness of genome scaffolds.
CONCLUSIONS: Our approach applies a sequential Bayesian updating technique to measure the similarity between optical maps and candidate contig paths. Using this similarity to guide path searching, our approach achieves higher accuracy than the existing \"searching by evaluation\" strategy that relies on heuristics. Furthermore, unlike the \"searching followed by evaluation\" strategy enumerating all possible paths, our approach prunes the unlikely sub-paths and extends the highly-probable ones only, thus significantly increasing searching efficiency.