Identification Of Structural Variants Research Articles

7030 Molecular Analysis Of Congenital Adrenal Hyperplasia-X Syndrome And Development Of A Pilot Panel For Analyzing Structural Variations With Long-Read Sequencing

Abstract Disclosure: J. Kim: None. S. Park: None. J. Yoon: None. D. Kim: None. S. Hwang: None. G. Kim: None. J. Kim: None. J. Choi: None. H. Yoo: None. Purpose: Genomic recombination events between the CYP21A2 and CYP21A1P genes are frequent due to their high sequence homology. Deletions in both the CYP21A2 and TNXB genes result in a chimeric TNXA/TNXB gene, leading to congenital adrenal hyperplasia (CAH)-X syndrome, characterized by a hypermobile form of Ehlers-Danlos syndrome. The aim of study was to determine the frequency of CAH-X syndrome and to develop a pilot panel for structural variation analysis using long-read sequencing technology. Methods: Among the 165 unrelated families with confirmed genetic mutations in the CYP21A2 gene, 44 probands had large deletions in one or both alleles. Long-range PCR was performed in 12 patients out of 44 probands using a forward primer for the 5’-UTR of the CYP21A2 and CYP21A1P and a reverse primer specific for exon 32 of TNXB. The amplified PCR products were then subjected to Sanger sequencing. We constructed a custom panel of 140 kb containing the RCCX modules arranged as STK19-C4A-CYP21A1P-TNXA-STK19B-C4B-CYP21A2-TNXB. In 4 patients with deletions in both the CYP21A2 and TNXB genes, long-read sequencing was performed using the custom panel on the PacBio Sequel II platform. Results: Out of 12 probands, eight harbored TNXA/TNXB chimeras. One patient was homozygous for CAH-X CH1 with a 120 bp deletion in exon 35 and had a Beighton score of 6 for joint hypermobility and multiple diverticula in the ascending colon. Two patients were heterozygous for CAH-X CH1, while three were heterozygous for the CAH-X CH2 with an intact exon 35 and the c.P4058W in exon 40. Two patients carried heterozygous mutations p.S4175N in exon 43, which is an unclassified type. Using long-read sequencing with a custom panel, missense mutations and TNXA/TNXB chimeras were detected in four patients previously identified by conventional direct sequencing and MLPA. Conclusions: This study identified 8 patients with CAH-X syndrome carrying four different TNXA/TNXB chimeras by long-range PCR. Long-read sequencing emerged as a comprehensive and efficient method for the molecular analysis of CAH, especially for the identification of structural variations. Biallelic deletion of TNXB was associated with severe clinical manifestations. Therefore, screening for CAH-X is essential for clinical management and prevention of the long-term consequences of CAH-X syndrome. Presentation: 6/1/2024

9266 Molecular Analysis Of Congenital Adrenal Hyperplasia-X Syndrome And Development Of A Pilot Panel For Analyzing Structural Variations With Long-Read Sequencing

Abstract Disclosure: J. Kim: None. S. Park: None. J. Yoon: None. D. Kim: None. S. Hwang: None. G. Kim: None. J. Kim: None. J. Choi: None. H. Yoo: None. Purpose: Genomic recombination events between the CYP21A2 and CYP21A1P genes are frequent due to their high sequence homology. Deletions in both the CYP21A2 and TNXB genes result in a chimeric TNXA/TNXB gene, leading to congenital adrenal hyperplasia (CAH)-X syndrome, characterized by a hypermobile form of Ehlers-Danlos syndrome. The aim of study was to determine the frequency of CAH-X syndrome and to develop a pilot panel for structural variation analysis using long-read sequencing technology. Methods: Among the 165 unrelated families with confirmed genetic mutations in the CYP21A2 gene, 44 probands had large deletions in one or both alleles. Long-range PCR was performed in 12 patients out of 44 probands using a forward primer for the 5’-UTR of the CYP21A2 and CYP21A1P and a reverse primer specific for exon 32 of TNXB. The amplified PCR products were then subjected to Sanger sequencing. We constructed a custom panel of 140 kb containing the RCCX modules arranged as STK19-C4A-CYP21A1P-TNXA-STK19B-C4B-CYP21A2-TNXB. In 4 patients with deletions in both the CYP21A2 and TNXB genes, long-read sequencing was performed using the custom panel on the PacBio Sequel II platform. Results: Out of 12 probands, eight harbored TNXA/TNXB chimeras. One patient was homozygous for CAH-X CH1 with a 120 bp deletion in exon 35 and had a Beighton score of 6 for joint hypermobility and multiple diverticula in the ascending colon. Two patients were heterozygous for CAH-X CH1, while three were heterozygous for the CAH-X CH2 with an intact exon 35 and the c.P4058W in exon 40. Two patients carried heterozygous mutations p.S4175N in exon 43, which is an unclassified type. Using long-read sequencing with a custom panel, missense mutations and TNXA/TNXB chimeras were detected in four patients previously identified by conventional direct sequencing and MLPA. Conclusions: This study identified 8 patients with CAH-X syndrome carrying four different TNXA/TNXB chimeras by long-range PCR. Long-read sequencing emerged as a comprehensive and efficient method for the molecular analysis of CAH, especially for the identification of structural variations. Biallelic deletion of TNXB was associated with severe clinical manifestations. Therefore, screening for CAH-X is essential for clinical management and prevention of the long-term consequences of CAH-X syndrome. Presentation: 6/1/2024

Should AI-Powered Whole-Genome Sequencing Be Used Routinely for Personalized Decision Support in Surgical Oncology—A Scoping Review

In this scoping review, we delve into the transformative potential of artificial intelligence (AI) in addressing challenges inherent in whole-genome sequencing (WGS) analysis, with a specific focus on its implications in oncology. Unveiling the limitations of existing sequencing technologies, the review illuminates how AI-powered methods emerge as innovative solutions to surmount these obstacles. The evolution of DNA sequencing technologies, progressing from Sanger sequencing to next-generation sequencing, sets the backdrop for AI’s emergence as a potent ally in processing and analyzing the voluminous genomic data generated. Particularly, deep learning methods play a pivotal role in extracting knowledge and discerning patterns from the vast landscape of genomic information. In the context of oncology, AI-powered methods exhibit considerable potential across diverse facets of WGS analysis, including variant calling, structural variation identification, and pharmacogenomic analysis. This review underscores the significance of multimodal approaches in diagnoses and therapies, highlighting the importance of ongoing research and development in AI-powered WGS techniques. Integrating AI into the analytical framework empowers scientists and clinicians to unravel the intricate interplay of genomics within the realm of multi-omics research, paving the way for more successful personalized and targeted treatments.

A Comparison of Structural Variant Calling from Short-Read and Nanopore-Based Whole-Genome Sequencing Using Optical Genome Mapping as a Benchmark.

The identification of structural variants (SVs) in genomic data represents an ongoing challenge because of difficulties in reliable SV calling leading to reduced sensitivity and specificity. We prepared high-quality DNA from 9 parent-child trios, who had previously undergone short-read whole-genome sequencing (Illumina platform) as part of the Genomics England 100,000 Genomes Project. We reanalysed the genomes using both Bionano optical genome mapping (OGM; 8 probands and one trio) and Nanopore long-read sequencing (Oxford Nanopore Technologies [ONT] platform; all samples). To establish a "truth" dataset, we asked whether rare proband SV calls (n = 234) made by the Bionano Access (version 1.6.1)/Solve software (version 3.6.1_11162020) could be verified by individual visualisation using the Integrative Genomics Viewer with either or both of the Illumina and ONT raw sequence. Of these, 222 calls were verified, indicating that Bionano OGM calls have high precision (positive predictive value 95%). We then asked what proportion of the 222 true Bionano SVs had been identified by SV callers in the other two datasets. In the Illumina dataset, sensitivity varied according to variant type, being high for deletions (115/134; 86%) but poor for insertions (13/58; 22%). In the ONT dataset, sensitivity was generally poor using the original Sniffles variant caller (48% overall) but improved substantially with use of Sniffles2 (36/40; 90% and 17/23; 74% for deletions and insertions, respectively). In summary, we show that the precision of OGM is very high. In addition, when applying the Sniffles2 caller, the sensitivity of SV calling using ONT long-read sequence data outperforms Illumina sequencing for most SV types.

Structural variant calling and clinical interpretation in 6224 unsolved rare disease exomes

Structural variants (SVs), including large deletions, duplications, inversions, translocations, and more complex events have the potential to disrupt gene function resulting in rare disease. Nevertheless, current pipelines and clinical decision support systems for exome sequencing (ES) tend to focus on small alterations such as single nucleotide variants (SNVs) and insertions-deletions shorter than 50 base pairs (indels). Additionally, detection and interpretation of large copy-number variants (CNVs) are frequently performed. However, detection of other types of SVs in ES data is hampered by the difficulty of identifying breakpoints in off-target (intergenic or intronic) regions, which makes robust identification of SVs challenging. In this paper, we demonstrate the utility of SV calling in ES resulting in a diagnostic yield of 0.4% (23 out of 5825 probands) for a large cohort of unsolved patients collected by the Solve-RD consortium. Remarkably, 8 out of 23 pathogenic SV were not found by comprehensive read-depth-based CNV analysis, resulting in a 0.13% increased diagnostic value.

Structural variants in linkage disequilibrium with GWAS-significant SNPs

With the recent expansion of structural variant identification in the human genome, understanding the role of these impactful variants in disease architecture is critically important. Currently, a large proportion of genome-wide-significant genome-wide association study (GWAS) single nucleotide polymorphisms (SNPs) are functionally unresolved, raising the possibility that some of these SNPs are associated with disease through linkage disequilibrium with causal structural variants. Hence, understanding the linkage disequilibrium between newly discovered structural variants and statistically significant SNPs may provide a resource for further investigation into disease-associated regions in the genome. Here we present a resource cataloging structural variant-significant SNP pairs in high linkage disequilibrium. The database is composed of (i) SNPs that have exhibited genome-wide significant association with traits, primarily disease phenotypes, (ii) newly released structural variants (SVs), and (iii) linkage disequilibrium values calculated from unphased data. All data files including those detailing SV and GWAS SNP associations and results of GWAS-SNP-SV pairs are available at the SV-SNP LD Database and can be accessed at ‵https://github.com/hliang-SchrodiLab/SV_SNPs. Our analysis results represent a useful fine mapping tool for interrogating SVs in linkage disequilibrium with disease-associated SNPs. We anticipate that this resource may play an important role in subsequent studies which investigate incorporating disease causing SVs into disease risk prediction models.

Graph-Based Pangenome of Actinidia chinensis Reveals Structural Variations Mediating Fruit Degreening.

Fruit ripening is associated with the degreening process (loss of chlorophyll) that occurs in most fruit species. Kiwifruit is one of the special species whose fruits may maintain green flesh by accumulating a large amount of chlorophyll even after ripening. However, little is known about the genetic variations related to the fruit degreening process. Here, a graph-based kiwifruit pangenome by analyzing 14 chromosome-scale haplotype-resolved genome assemblies from seven representative cultivars or lines in Actinidia chinensis is built. A total of 49,770 non-redundant gene families are identified, with core genes constituting 46.6%, and dispensable genes constituting 53.4%. A total of 84,591 non-redundant structural variations (SVs) are identified. The pangenome graph integrating both reference genome sequences and variant information facilitates the identification of SVs related to fruit color. The SV in the promoter of the AcBCM gene determines its high expression in the late developmental stage of fruits, which causes chlorophyll accumulation in the green-flesh fruits by post-translationally regulating AcSGR2, a key enzyme of chlorophyll catabolism. Taken together, a high-quality pangenome is constructed, unraveled numerous genetic variations, and identified a novel SV mediating fruit coloration and fruit quality, providing valuable information for further investigating genome evolution and domestication, QTL genes function, and genomics-assisted breeding.

Whole-genome sequencing analysis in fetal structural anomalies: novel phenotype-genotype discoveries.

The identification of structural variants and single-nucleotide variants is essential in finding molecular etiologies of monogenic genetic disorders. Whole-genome sequencing (WGS) is becoming more widespread in genetic disease diagnosis. However, data on its clinical utility remain limited in prenatal practice. We aimed to expand our understanding of implementing WGS in the genetic diagnosis of fetal structural anomalies. We employed trio WGS with a minimum coverage of 40× on the MGI DNBSEQ-T7 platform in a cohort of 17 fetuses presenting with aberrations detected by ultrasound, but uninformative findings of standard chromosomal microarray analysis (CMA) and exome sequencing (ES). Causative genetic variants were identified in two families, with an increased diagnostic yield of 11.8% (2/17). Both were exon-level copy-number variants of small size (3.03 kb and 5.16 kb) and beyond the detection thresholds of CMA and ES. Moreover, to the best of our knowledge, we have described the first prenatal instance of the association of FGF8 with holoprosencephaly and facial deformities. Our analysis demonstrates the clinical value of WGS in the diagnosis of the underlying etiology of fetuses with structural abnormalities, when routine genetic tests have failed to provide a diagnosis. Additionally, the novel variants and new fetal manifestations have expanded the mutational and phenotypic spectrums of BBS9 and FGF8. © 2023 International Society of Ultrasound in Obstetrics and Gynecology.

Tradeoffs in alignment and assembly-based methods for structural variant detection with long-read sequencing data

Long-read sequencing offers long contiguous DNA fragments, facilitating diploid genome assembly and structural variant (SV) detection. Efficient and robust algorithms for SV identification are crucial with increasing data availability. Alignment-based methods, favored for their computational efficiency and lower coverage requirements, are prominent. Alternative approaches, relying solely on available reads for de novo genome assembly and employing assembly-based tools for SV detection via comparison to a reference genome, demand significantly more computational resources. However, the lack of comprehensive benchmarking constrains our comprehension and hampers further algorithm development. Here we systematically compare 14 read alignment-based SV calling methods (including 4 deep learning-based methods and 1 hybrid method), and 4 assembly-based SV calling methods, alongside 4 upstream aligners and 7 assemblers. Assembly-based tools excel in detecting large SVs, especially insertions, and exhibit robustness to evaluation parameter changes and coverage fluctuations. Conversely, alignment-based tools demonstrate superior genotyping accuracy at low sequencing coverage (5-10×) and excel in detecting complex SVs, like translocations, inversions, and duplications. Our evaluation provides performance insights, highlighting the absence of a universally superior tool. We furnish guidelines across 31 criteria combinations, aiding users in selecting the most suitable tools for diverse scenarios and offering directions for further method development.

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.

Optical Genome Mapping for Comprehensive Cytogenetic Analysis of Soft-Tissue and Bone Tumors for Diagnostic Purposes

Soft tissue and bone tumours represent a heterogeneous group of tumours encompassing more than 100 histological subtypes today. Identifying genetic aberrations is increasingly important in these tumours for accurate diagnosis. While gene mutations are typically detected by second generation sequencing, the identification of structural variants (SVs) and copy number alterations (CNAs) remains challenging and requires various cytogenetic techniques including karyotyping, fluorescent in situ hybridisation and arrays, each having important limitations.We applied Optical Genome Mapping (OGM), a non-sequencing-based technique for high-resolution detection of SVs and CNAs in a retrospective series of diagnostic soft tissue and bone tumour samples. Sample preparation was successful in 38 out of 53 cases, with the highest success rate in non-adipocytic soft tissue tumours (24/27 cases, 89%). In 32 out of 35 cases carrying a diagnostic SV or CNA, OGM identified the aberration (91%) including a POU2AF3::EWSR1 fusion in a round cell sarcoma and a translocation t(1;5)(p22;p15) in a myxoinflammatory fibroblastic sarcoma. Interestingly, OGM shed light on the genomic complexity underlying the various aberrations. In five samples OGM showed that chains of rearrangements generated the diagnostic fusion, three of which involved chromoplexy. Additionally, in nine samples chromothripsis was causal to the formation of giant marker/ring/double minute chromosomes. Finally, compared to standard-of-care cytogenetics, OGM revealed additional aberrations, requiring further investigation of their potential clinical relevance.

Haplotype information of large neuromuscular disease genes provided by linked-read sequencing has a potential to increase diagnostic yield.

Rare or novel missense variants in large genes such as TTN and NEB are frequent in the general population, which hampers the interpretation of putative disease-causing biallelic variants in patients with sporadic neuromuscular disorders. Often, when the first initial genetic analysis is performed, the reconstructed haplotype, i.e. phasing information of the variants is missing. Segregation analysis increases the diagnostic turnaround time and is not always possible if samples from family members are lacking. To overcome this difficulty, we investigated how well the linked-read technology succeeded to phase variants in these large genes, and whether it improved the identification of structural variants. Linked-read sequencing data of nemaline myopathy, distal myopathy, and proximal myopathy patients were analyzed for phasing, single nucleotide variants, and structural variants. Variant phasing was successful in the large muscle genes studied. The longest continuous phase blocks were gained using high-quality DNA samples with long DNA fragments. Homozygosity increased the number of phase blocks, especially in exome sequencing samples lacking intronic variation. In our cohort, linked-read sequencing added more information about the structural variation but did not lead to a molecular genetic diagnosis. The linked-read technology can support the clinical diagnosis of neuromuscular and other genetic disorders.

Kled: an ultra-fast and sensitive structural variant detection tool for long-read sequencing data.

Structural Variants (SVs) are a crucial type of genetic variant that can significantly impact phenotypes. Therefore, the identification of SVs is an essential part of modern genomic analysis. In this article, we present kled, an ultra-fast and sensitive SV caller for long-read sequencing data given the specially designed approach with a novel signature-merging algorithm, custom refinement strategies and a high-performance program structure. The evaluation results demonstrate that kled can achieve optimal SV calling compared to several state-of-the-art methods on simulated and real long-read data for different platforms and sequencing depths. Furthermore, kled excels at rapid SV calling and can efficiently utilize multiple Central Processing Unit (CPU) cores while maintaining low memory usage. The source code for kled can be obtained from https://github.com/CoREse/kled.

Investigation of chromosomal genetic characteristics and identification of structural variation in the offspring of hexaploid triticale×hexaploid wheat.

Hexaploid triticale is an important genetic resource for genetic improvement of common wheat, which can broaden the genetic basis of wheat. In order to lay a foundation for the subsequent research and utilization of triticale germplasm materials, the chromosomal genetic characteristics of cross and backcross offspring of hexaploid triticale×hexaploid wheat were investigated in the process of transferring rye chromatin from hexaploid triticale to hexaploid wheat. Hybrid and backcross combinations were prepared with hexaploid triticale 16yin171 as the maternal parent and hexaploid wheat Chuanmai62 as the paternal parent. The chromosomes in root tip cells of F1, BC1F1 and BC1F2 plants were traced and identified non-denaturing florescence in situ hybridization (ND-FISH). The results indicated that the backcross setting rate of hybrid F1 was 2.61%. The transmission frequency of 2R chromosome was the highest in BC1F1 plants while the transmissibility of rye chromosome in BC1F2 plant was 6R>4R>2R, and the 5B-7B wheat translocation in BC1F2 plants showed severe segregation. A total of 24 structural variant chromosomes were observed both in BC1F1 and BC1F2 plants, including chromosome fragments, isochromosomes, translocations, and dicentric chromosomes. In addition, the seed length and 1000-grain weight of some BC1F2 plants were better than that of the hexaploid wheat parent Chuanmai 62. Therefore, multiple backcrosses should be adopted as far as possible to make the rapid recovery of group D chromosomes, ensuring the recovery of fertility in offspring, when hexaploid tritriale is used as a bridge to introduce rye genetic material into common wheat. At the same time, the potential application value of chromosomal structural variation materials should be also concerned.

Whole genome sequencing enables new genetic diagnosis for inherited retinal diseases by identifying pathogenic variants

Inherited retinal diseases (IRDs) are a group of common primary retinal degenerative disorders. Conventional genetic testing strategies, such as panel-based sequencing and whole exome sequencing (WES), can only elucidate the genetic etiology in approximately 60% of IRD patients. Studies have suggested that unsolved IRD cases could be attributed to previously undetected structural variants (SVs) and intronic variants in IRD-related genes. The aim of our study was to obtain a definitive genetic diagnosis by employing whole genome sequencing (WGS) in IRD cases where the causative genes were inconclusive following an initial screening by panel sequencing. A total of 271 unresolved IRD patients and their available family members (n = 646) were screened using WGS to identify pathogenic SVs and intronic variants in 792 known ocular disease genes. Overall, 13% (34/271) of IRD patients received a confirmed genetic diagnosis, among which 7% were exclusively attributed to SVs, 4% to a combination of single nucleotide variants (SNVs) and SVs while another 2% were linked to intronic variants. 22 SVs, 3 deep-intronic variants, and 2 non-canonical splice-site variants across 14 IRD genes were identified in the entire cohort. Notably, all of these detected SVs and intronic variants were novel pathogenic variants. Among those, 74% (20/27) of variants were found in genes causally linked to Retinitis Pigmentosa (RP), with the gene EYS being the most frequently affected by SVs. The identification of SVs and intronic variants through WGS enhances the genetic diagnostic yield of IRDs and broadens the mutational spectrum of known IRD-associated genes.

Identification of the genetic characteristics of copy number variations in experimental specific pathogen-free ducks using whole-genome resequencing.

Specific pathogen-free ducks are a valuable laboratory resource for waterfowl disease research and poultry vaccine development. High throughput sequencing allows the systematic identification of structural variants in genomes. Copy number variation (CNV) can explain the variation of important duck genetic traits. Herein, the genome-wide CNVs of the three experimental duck species in China (Jinding ducks (JD), Shaoxing ducks (SX), and Fujian Shanma ducks (SM)) were characterized using resequencing to determine their genetic characteristics and selection signatures. We obtained 4,810 CNV regions (CNVRs) by merging 73,012 CNVs, covering 4.2% of the duck genome. Functional analysis revealed that the shared CNVR-harbored genes were significantly enriched for 31 gene ontology terms and 16 Kyoto Encyclopedia of Genes and Genomes pathways (e.g., olfactory transduction and immune system). Based on the genome-wide fixation index for each CNVR, growth (SPAG17 and PTH1R), disease resistance (CATHL3 and DMBT1), and thermoregulation (TRPC4 and SLIT3) candidate genes were identified in strongly selected signatures specific to JD, SM, and SX, respectively. In conclusion, we investigated the genome-wide distribution of experimental duck CNVs, providing a reference to establish the genetic basis of different phenotypic traits, thus contributing to the management of experimental animal genetic resources.

Chromosomal scale assembly reveals localized structural variants in avian caecal coccidian parasite Eimeria tenella

Eimeria tenella is a major cause of caecal coccidiosis in commercial poultry chickens worldwide. Here, we report chromosomal scale assembly of Eimeria tenella strain APU2, a strain isolated from commercial broiler chickens in the U.S. We obtained 100× sequencing Oxford Nanopore Technology (ONT) and more than 800× Coverage of Illumina Next-Seq. We created the assembly using the hybrid approach implemented in MaSuRCA, achieving a contiguous 51.34 Mb chromosomal-scale scaffolding enabling identification of structural variations. The AUGUSTUS pipeline predicted 8060 genes, and BUSCO deemed the genomes 99% complete; 6278 (78%) genes were annotated with Pfam domains, and 1395 genes were assigned GO-terms. Comparing E. tenella strains (APU2, US isolate and Houghton, UK isolate) derived Houghton strain of E. tenella revealed 62,905 high stringency differences, of which 45,322 are single nucleotide polymorphisms (SNPs) (0.088%). The rate of transitions/transversions among the SNPs are 1.63 ts/tv. The strains possess conserved gene order but have profound sequence heterogeneity in a several chromosomal segments (chr 2, 11 and 15). Genic and intergenic variation in defined gene families was evaluated between the two strains to possibly identify sequences under selection. The average genic nucleotide diversity of 2.8 with average 2 kb gene length (0.145%) at genic level. We examined population structure using available E. tenella sequences in NCBI, revealing that the two E. tenella isolates from the U.S. (E. tenella APU2 and Wisconsin, “ERR296879”) share a common maternal inheritance with the E. tenella Houghton. Our chromosomal level assembly promotes insight into Eimeria biology and evolution, hastening drug discovery and vaccine development.

Selected Genomic Structural Variants Refine ELN-Based Prognostic Stratification of Patients with Acute Myeloid Leukemia and Normal Karyotype

Background. Normal karyotype Acute Myeloid Leukemia (nk-AML) accounts for 40% of all AML. Conventionally, nk-AML patients (pts) have been associated with the ELN favorable and intermediate risk category, characterized by extreme prognostic heterogeneity, representing an unmet therapeutic need especially as regards effective positioning of allogeneic transplantation (ASCT) as consolidation treatment. Aim. To improve risk stratification of nk-AML, on top of 2017 ELN criteria, by identification of structural variants (SV) with prognostic significance through the analysis of whole genome sequencing by long reads Nanopore platform. Patients and Methods. A total of 247 nk-AML pts receiving intensive therapy was included. The learning cohort included 95 pts from the prospective NILG 02/06 trial ( Bassan R Blood Adv 2019; 3:1103) comparing standard vs high-dose chemotherapy and 67 pts from the prospective GIMEMA AML1310 trial of risk-adapted, MRD-directed therapy ( Venditti A, Blood 2019;134:935). The validation cohort comprised 85 pts from Florence database. Whole genome long-read nanopore sequencing was performed on GridION platform to a median depth of 5x. After alignment to hgr38 genome, only those SV that had been concurrently identified by 4 independent callers were retained for analysis. Results. In the whole series (WS),197 pts (79.7%) obtained CR, 91 (46.2%) relapsed; 50 pts (20.2%) were primary refractory, 83 (33.6%) underwent ASCT. According to ELN criteria, 56.7%, 29.2% and 14.1% of the pts were in the favorable, intermediate and adverse risk category. Median survival (OS) was 16.9mo (9-24.7) in adverse risk category, 24.1mo (4.5-43.7) intermediate, and not reached in favorable risk category (P= 0.00007). However, adverse and intermediate category did not differ significantly (P=0.63), as expected considering the selection of nk-AML. Extensive filtering against 100 healthy donors and publicly available datasets of genomic variants to remove SV with >0.01% allele frequency resulted in 2,038 SV; after removal of private SV (ie, present in ≤2 pt), 122 SV were finally retained. Univariate regression analysis resulted in 10 SV associated with OS, of which 7 were validated with independent technology (Sanger and high-resolution melting, HRM). Multivariate analysis including all ELN-risk score variables showed that 5 of the 7 SV were independently associated with OS (hence, referred as high-risk variants, HRV). Three HRV affected the locus of coding genes on Chr4 q32.3 (inversion spanning 6,103bp), Chr5 p12 (333bp insertion) and Chr9 q34.3 (57bp deletion); Chr3 q26.1 (64bp insertion) in a Long Intergenic Non-Protein Coding RNA gene; Chr2 p13.2 (64bp deletion), in intergenic region. Presence of HRV impacted on OS with HR of 4.1 (95%CI,2.4-7; P=1.5e-7) in the learning cohort and HR 3.4 (95%CI, 1.5-7.6; P=0.003) in the validation cohort. Censoring at ASCT had no impact in either cohort. In total, 29 pts (11.7%) were HRV+, and their OS was 12.6mo (95%CI, 5.4-19.9) vs not reached (95%CI, 33.5-40.9; P=8.4183e-11) in HRV- pts (HR 3.9, 95%CI, 2.5-6; P=1.6261e-9) (Figure 1). DFS and EFS was 7mo (95%CI: 3.6-10.5) and 14.6mo (95%CI,2.1-27) in HRV+ pts vs not reached (95%CI, 31.7-40) and 30mo (95%CI: 29.9-30.1) (P<0.01 for both). Also, the rate of relapse was higher among HRV+, 58.6% vs 34.4% (P=0.01), with a trend to lower rate of CR attainment (72.4% vs 82.6%). There was no remarkable difference between HRV+ and HRV- pts as regarded frequency and type of ELN molecular variables. We finally evaluated whether integration of HRV within ELN risk score might improve the predictive performance of the latter. The resulting model enlisted 4 tiers, favorable (median OS not reached), intermediate (27.4mo, 95%CI: 3.6-51.1, HR:2.4; 95%CI,1.5-3.8), adverse (21.5mo, 95%CI: 5.4-37.6, HR:2.5; 95%CI,1.4-4.3) and HRV+ (12.6mo, 95%CI: 5.4-19.9, HR:5.9; 95%CI,3.6-9.8) categories (P=1.3395e-12) (Figure 2). Of note, the HRV+ category included 79.3% of pts otherwise categorized as ELN favorable or intermediate. Conclusions. We have identified, by long-read whole genome sequencing, a set of 5 structural variants that marks a subgroup of nk-AML pts with outmost dismal prognosis and may be integrated in ELN-risk score to help therapeutic decisions. Since HRV can be conveniently interrogated by routine approaches such as Sanger sequencing and HRM, further studies on larger cohorts might support these findings.

Accurate identification of structural variations from cancer samples.

Structural variations (SVs) are commonly found in cancer genomes. They can cause gene amplification, deletion and fusion, among other functional consequences. With an average read length of hundreds of kilobases, nano-channel-based optical DNA mapping is powerful in detecting large SVs. However, existing SV calling methods are not tailored for cancer samples, which have special properties such as mixed cell types and sub-clones. Here we propose the Cancer Optical Mapping for detecting Structural Variations (COMSV) method that is specifically designed for cancer samples. It shows high sensitivity and specificity in benchmark comparisons. Applying to cancer cell lines and patient samples, COMSV identifies hundreds of novel SVs per sample.

Searching for sequencing signal anomalies associated with genome structural variations

Genomic structural variations (SVs) are one of the main sources of genetic diversity. Structural variants as mutagens may have a significant impact on human health and lead to hereditary diseases and cancers. Existing methods of finding structural variants are based on analysis of high-throughput sequencing data and despite significant progress in the development of the detection methods, there is still a need for improving the identification of structural variations with accuracy appropriate for use in a diagnostic procedure. Analysis of the signal of sequencing coverage (i.e., the number of sequencing fragments that aligned to every point of a genome) holds new potential for the design of approaches for structural variations discovery, and can be used as time-series analysis. Here, we present an approach for identification of patterns in the coverage signal. The method has been developed based on algorithms used for analysis of time series data, namely KNN (K-nearest neighbour) search algorithm and the SAX (Symbolic Aggregation Approximation) method. Using the rich dataset encompassing full genomes of 911 individuals with different ethnic backgrounds generated by the Human Genome Diversity Project initiative, we constructed generalized patterns of signal coverage in the vicinity of breakpoints corresponding to various structural variant types. Also, with the benefit of the SAX models of the motifs we developed a software package for fast detection of anomalies in the coverage signal.