Repetitive Regions Research Articles

Large mitochondrial genomes in tenthredinid sawflies (Hymenoptera, Tenthredinidae)

We sequenced and assembled mitochondrial genomes of three tenthredinid sawflies (Euura poecilonota, E. striata, and Dolerus timidus) using Oxford Nanopore Technologies’ MinION. The Canu assembler produced circular assemblies (23,000–40,000 bp). Still, errors were found in the highly repetitive non-coding control region because of the fragmented DNA which led to no reads spanning the complete control region, preventing its reliable assembly. Based on the non-repetitive coding region’s sequencing coverage, we estimate the lengths of mitochondrial genomes of E. poecilonota, D. timidus, and E. striata to be about 30,000 bp, 31,000 bp, and 37,000 bp and control region to be 15,000 bp, 16,000 bp, and 22,000 bp respectively. All standard bilaterian mitochondrial genes are in the same order and orientation, except trnQ, which is on the minus strand in Euura and the plus strand in Dolerus. Using published tenthredinid genome data, we show that control region lengths are often underestimated.

Sequencing Strategy to Ensure Accurate Plasmid Assembly.

Despite the wide use of plasmids in research and clinical production, the need to verify plasmid sequences is a bottleneck that is too often underestimated in the manufacturing process. Although sequencing platforms continue to improve, the method and assembly pipeline chosen still influence the final plasmid assembly sequence. Furthermore, few dedicated tools exist for plasmid assembly, especially for de novo assembly. Here, we evaluated short-read, long-read, and hybrid (both short and long reads) de novo assembly pipelines across three replicates of a 24-plasmid library. Consistent with previous characterizations of each sequencing technology, short-read assemblies had issues resolving GC-rich regions, and long-read assemblies commonly had small insertions and deletions, especially in repetitive regions. The hybrid approach facilitated the most accurate, consistent assembly generation and identified mutations relative to the reference sequence. Although Sanger sequencing can be used to verify specific regions, some GC-rich and repetitive regions were difficult to resolve using any method, suggesting that easily sequenced genetic parts should be prioritized in the design of new genetic constructs.

Leveraging the T2T assembly to resolve rare and pathogenic inversions in reference genome gaps.

Chromosomal inversions (INVs) are particularly challenging to detect due to their copy-number neutral state and association with repetitive regions. Inversions represent about 1/20 of all balanced structural chromosome aberrations and can lead to disease by gene disruption or altering regulatory regions of dosage-sensitive genes in cis Short-read genome sequencing (srGS) can only resolve ∼70% of cytogenetically visible inversions referred to clinical diagnostic laboratories, likely due to breakpoints in repetitive regions. Here, we study 12 inversions by long-read genome sequencing (lrGS) (n = 9) or srGS (n = 3) and resolve nine of them. In four cases, the inversion breakpoint region was missing from at least one of the human reference genomes (GRCh37, GRCh38, T2T-CHM13) and a reference agnostic analysis was needed. One of these cases, an INV9 mappable only in de novo assembled lrGS data using T2T-CHM13 disrupts EHMT1 consistent with a Mendelian diagnosis (Kleefstra syndrome 1; MIM#610253). Next, by pairwise comparison between T2T-CHM13, GRCh37, and GRCh38, as well as the chimpanzee and bonobo, we show that hundreds of megabases of sequence are missing from at least one human reference, highlighting that primate genomes contribute to genomic diversity. Aligning population genomic data to these regions indicated that these regions are variable between individuals. Our analysis emphasizes that T2T-CHM13 is necessary to maximize the value of lrGS for optimal inversion detection in clinical diagnostics. These results highlight the importance of leveraging diverse and comprehensive reference genomes to resolve unsolved molecular cases in rare diseases.

Resolution of ring chromosomes, Robertsonian translocations, and complex structural variants from long-read sequencing and telomere-to-telomere assembly.

Delineation of structural variants (SVs) at sequence resolution in highly repetitive genomic regions has long been intractable. The sequence properties, origins, and functional effects of classes of genomic rearrangements such as ring chromosomes and Robertsonian translocations thus remain unknown. To resolve these complex structures, we leveraged several recent milestones in the field, including (1) the emergence of long-read sequencing, (2) the gapless telomere-to-telomere (T2T) assembly, and (3) a tool (BigClipper) to discover chromosomal rearrangements from long reads. We applied these technologies across 13 cases with ring chromosomes, Robertsonian translocations, and complex SVs that were unresolved by short reads, followed by validation using optical genome mapping (OGM). Our analyses resolved 10 of 13 cases, including a Robertsonian translocation and all ring chromosomes. Multiple breakpoints were localized to genomic regions previously recalcitrant to sequencing such as acrocentric p-arms, ribosomal DNA arrays, and telomeric repeats, and involved complex structures such as a deletion-inversion and interchromosomal dispersed duplications. We further performed methylation profiling from long-read data to discover phased differential methylation in a gene promoter proximal to a ring fusion, suggesting a long-range position effect (LRPE) with heterochromatin spreading. Breakpoint sequences suggested mechanisms of SV formation such as microhomology-mediated and non-homologous end-joining, as well as non-allelic homologous recombination. These methods provide some of the first glimpses into the sequence resolution of Robertsonian translocations and illuminate the structural diversity of ring chromosomes and complex chromosomal rearrangements with implications for genome biology, prediction of LRPEs from integrated multi-omics technologies, and molecular diagnostics in rare disease cases.

First De Novo genome assembly and characterization of Gaultheria prostrata.

Gaultheria Kalm ex L. (Ericaceae), a type of evergreen shrub, known as a natural source of methyl salicylate, possesses rich germplasm resources, strong habitat adaptability, significant ornamental value, and noteworthy pharmacological activities. However, due to the paucity of whole genomic information, genetically deep research in these areas remains limited. Consequently, we intend to obtain genome data through high-throughput sequencing, gene annotation, flow cytometry, transcription factors prediction and genetic marker analysis for a representative species of this genus, with Gaultheria prostrata selected for our study. In this study, we preliminarily obtained the genome of G. prostrata through next-generation sequencing methods. Utilizing 47.94 Gb of high-quality sequence data (108.95× coverage), assembled into 114,436 scaffolds, with an N50 length of 33,667 bp. The genome size assembled by SOAPdenovo, approximately 417 Mb, corresponded closely to predictions by flow cytometry (440 Mb) and k-mer analysis (447 Mb). The genome integrity was evaluated using BUSCO with 91%. The heterozygosity ratio was 0.159%, the GC content was 38.85%, and the repetitive regions encompassed over 34.6% of the genome. A total of 26,497 protein-coding genes have been predicted and annotated across Nr, Swissprot, GO, KEGG, and Pfam databases. Among these, 14,377 and 2,387 genes received functional annotation in Nr and Swissprot, respectively; 21,895, 24,424, and 22,330 genes were similarly annotated in GO, KEGG, and Pfam. Moreover, A total of 279,785 SSRs were identified and 345,270 primers for these SSRs were designed. Within the various nucleotide types of SSRs, AG/CT and AAG/CTT constituted the predominant dinucleotide and trinucleotide repeat types in G. prostrata. In addition, 1,395 transcription factors (TFs) from 75 TF families, 462 transcription regulators (TRs) from 33 TR families and 840 protein kinase (PKs) from 118 PK families were identified in this genome. We also performed phylogenetic analyses of G. prostrata and related species, including estimation of divergence times and expansion and contraction analyses, followed by positive selection analyses of orthologous gene pairs of G. prostrata and its close relative Vaccinium corymbosum. These results provide a reference for in-depth study of genus Gaultheria, contributing to future functional and comparative genomics analyses and providing supporting data for the development of molecular markers.

Geometric deep learning framework for de novo genome assembly.

The critical stage of every de novo genome assembler is identifying paths in assembly graphs that correspond to the reconstructed genomic sequences. The existing algorithmic methods struggle with this, primarily due to repetitive regions causing complex graph tangles, leading to fragmented assemblies. Here, we introduce GNNome, a framework for path identification based on geometric deep learning that enables training models on assembly graphs without relying on existing assembly strategies. By leveraging only the symmetries inherent to the problem, GNNome reconstructs assemblies from PacBio HiFi reads with contiguity and quality comparable to those of the state-of-the-art tools across several species. With every new genome assembled telomere-to-telomere, the amount of reliable training data at our disposal increases. Combining the straightforward generation of abundant simulated data for diverse genomic structures with the AI approach makes the proposed framework a plausible cornerstone for future work on reconstructing complex genomes with different ploidy and aneuploidy degrees. To facilitate such developments, we make the framework and the best-performing model publicly available, provided as a tool that can directly be used to assemble new haploid genomes.

Long-read genome assembly of the insect model organism Tribolium castaneum reveals spread of satellite DNA in gene-rich regions by recurrent burst events.

Eukaryotic genomes are replete with satellite DNAs (satDNAs), large stretches of tandemly repeated sequences that are mostly underrepresented in genome assemblies. Here we combined nanopore long-read sequencing with a reference-guided assembly approach to generate an improved, high-quality genome assembly, TcasONT, of the model beetle Tribolium castaneum Enriched by 45 Mb in repetitive regions, the new assembly comprises almost the entire genome sequence. We use the enhanced assembly to conduct global and in-depth analyses of abundant euchromatic satDNAs. Unexpectedly, we show the extensive spread of satDNAs in gene-rich regions, including long arrays. The sequence similarity relationships between satDNA monomers and arrays indicate a recent exchange of satDNA arrays between different chromosomes. We propose a scenario of their genome dynamics characterized by repeated bursts of satDNAs spreading through euchromatin, followed by a process of elongation and homogenization of arrays. We find that suppressed recombination on the X Chromosome has no significant effect on the spread of satDNAs but the X rather tolerates the amplification of satDNAs into longer arrays. Analyses of arrays' neighboring regions show a tendency of one satDNA to be associated with transposable-like elements. Using 2D electrophoresis followed by Southern blotting, we prove Cast satDNAs' presence in the fraction of extrachromosomal circular DNA (eccDNA). We point to two mechanisms that enable this satDNA spread to occur: transposition by transposable elements and insertion mediated by eccDNA. The presence of such a large proportion of satDNA in gene-rich regions inevitably gives rise to speculation about their possible influence on gene expression.

Pixel-level Terrain Processing of the Martian Surface from Moderate Resolution Images of Tianwen-1

The moderate-resolution camera (MoRIC) of the Tianwen-1 orbiter, China’s first Mars exploration mission, is a frame-imaging scheme color camera. However, generating a precise digital elevation model (DEM) from these images faces challenges due to the presence of featureless and repetitive regions on the Martian surface. Traditional photogrammetric methods often struggle to achieve pixel-level resolution in these areas. To address this, we employ a shape from shading (SFS) algorithm that leverages shading patterns to reconstruct fine-scale terrain details, optimizing photogrammetric initial DEM. This paper presents a novel global bisection search algorithm, based on the Pearson correlation coefficient to determine the smoothing parameter, a crucial element in the SFS process. Comparisons with higher-resolution data from the Mars Express high-resolution stereo camera and Mars Reconnaissance Orbiter CTX images validate our approach, highlighting the potential of SFS to significantly enhance the scientific value of Tianwen-1 MoRIC data by generating high-resolution, three-dimensional maps of Mars.

Centromere Landscapes Resolved from Hundreds of Human Genomes.

High-fidelity (HiFi) sequencing has facilitated the assembly and analysis of the most repetitive region of the genome, the centromere. Nevertheless, our current understanding of human centromeres is based on a relatively small number of telomere-to-telomere assemblies, which has not yet captured its full diversity. In this study, we investigated the genomic diversity of human centromere higher order repeats (HORs) via both HiFi reads and haplotype-resolved assemblies from hundreds of samples drawn from ongoing pangenome-sequencing projects and reprocessed them via a novel HOR annotation pipeline, HiCAT-human. We used this wealth of data to provide a global survey of the centromeric HOR landscape; in particular, we found that 23 HORs presented significant copy number variability between populations. We detected three centromere genotypes with unbalanced population frequencies on chromosomes 5, 8, and 17. An inter-assembly comparison of HOR loci further revealed that while HOR array structures are diverse, they nevertheless tend to form a number of specific landscapes, each exhibiting different levels of HOR subunit expansion and possibly reflecting a cyclical evolutionary transition from homogeneous to nested structures and back.

Benchmarking reveals superiority of deep learning variant callers on bacterial nanopore sequence data.

Variant calling is fundamental in bacterial genomics, underpinning the identification of disease transmission clusters, the construction of phylogenetic trees, and antimicrobial resistance detection. This study presents a comprehensive benchmarking of variant calling accuracy in bacterial genomes using Oxford Nanopore Technologies (ONT) sequencing data. We evaluated three ONT basecalling models and both simplex (single-strand) and duplex (dual-strand) read types across 14 diverse bacterial species. Our findings reveal that deep learning-based variant callers, particularly Clair3 and DeepVariant, significantly outperform traditional methods and even exceed the accuracy of Illumina sequencing, especially when applied to ONT's super-high accuracy model. ONT's superior performance is attributed to its ability to overcome Illumina's errors, which often arise from difficulties in aligning reads in repetitive and variant-dense genomic regions. Moreover, the use of high-performing variant callers with ONT's super-high accuracy data mitigates ONT's traditional errors in homopolymers. We also investigated the impact of read depth on variant calling, demonstrating that 10× depth of ONT super-accuracy data can achieve precision and recall comparable to, or better than, full-depth Illumina sequencing. These results underscore the potential of ONT sequencing, combined with advanced variant calling algorithms, to replace traditional short-read sequencing methods in bacterial genomics, particularly in resource-limited settings.

ULTRA-Effective labeling of tandem repeats in genomic sequence

Abstract In the age of long read sequencing, genomics researchers now have access to accurate repetitive DNA sequence (including satellites) that, due to the limitations of short read sequencing, could previously be observed only as unmappable fragments. Tools that annotate repetitive sequence are now more important than ever, so that we can better understand newly uncovered repetitive sequences, and also so that we can mitigate errors in bioinformatic software caused by those repetitive sequences. To that end, we introduce the 1.0 release of our tool for identifying and annotating locally-repetitive sequence, ULTRA (ULTRA Locates Tandemly Repetitive Areas). ULTRA is fast enough to use as part of an efficient annotation pipeline, produces state-of-the-art reliable coverage of repetitive regions containing many mutations, and provides interpretable statistics and labels for repetitive regions. It is released under an open license, and is available for download at https://github.com/TravisWheelerLab/ULTRA

Nanopore sequencing with unique molecular identifiers enables accurate mutation analysis and haplotyping in the complex lipoprotein(a) KIV-2 VNTR.

Repetitive genome regions, such as variable number of tandem repeats (VNTR) or short tandem repeats (STR), are major constituents of the uncharted dark genome and evade conventional sequencing approaches. The protein-coding LPA kringle IV type-2 (KIV-2) VNTR (5.6kb per unit, 1-40 units per allele) is a medically highly relevant example with a particularly intricate structure, multiple haplotypes, intragenic homologies, and an intra-VNTR STR. It is the primary regulator of plasma lipoprotein(a) [Lp(a)] concentrations, an important cardiovascular risk factor. Lp(a) concentrations vary widely between individuals and ancestries. Multiple variants and functional haplotypes in the LPA gene and especially in the KIV-2 VNTR strongly contribute to this variance. We evaluated the performance of amplicon-based nanopore sequencing with unique molecular identifiers (UMI-ONT-Seq) for SNP detection, haplotype mapping, VNTR unit consensus sequence generation, and copy number estimation via coverage-corrected haplotypes quantification in the KIV-2 VNTR. We used 15 human samples and low-level mixtures (0.5 to 5%) of KIV-2 plasmids as a validation set. We then applied UMI-ONT-Seq to extract KIV-2 VNTR haplotypes in 48 multi-ancestry 1000 Genome samples and analyzed at scale a poorly characterized STR within the KIV-2 VNTR. UMI-ONT-Seq detected KIV-2 SNPs down to 1% variant level with high sensitivity, specificity, and precision (0.977 ± 0.018; 1.000 ± 0.0005; 0.993 ± 0.02) and accurately retrieved the full-length haplotype of each VNTR unit. Human variant levels were highly correlated with next-generation sequencing (R2 = 0.983) without bias across the whole variant level range. Six reads per UMI produced sequences of each KIV-2 unit with Q40 quality. The KIV-2 repeat number determined by coverage-corrected unique haplotype counting was in close agreement with droplet digital PCR (ddPCR), with 70% of the samples falling even within the narrow confidence interval of ddPCR. We then analyzed 62,679 intra-KIV-2 STR sequences and explored KIV-2 SNP haplotype patterns across five ancestries. UMI-ONT-Seq accurately retrieves the SNP haplotype and precisely quantifies the VNTR copy number of each repeat unit of the complex KIV-2 VNTR region across multiple ancestries. This study utilizes the KIV-2 VNTR, presenting a novel and potent tool for comprehensive characterization of medically relevant complex genome regions at scale.

Effects of Mini-Spidroin Repeat Region on the Mechanical Properties of Artificial Spider Silk Fibers.

Spiders can produce up to seven different types of silk, each with unique mechanical properties that stem from variations in the repetitive regions of spider silk proteins (spidroins). Artificial spider silk can be made from mini-spidroins in an all-aqueous-based spinning process, but the strongest fibers seldom reach more than 25% of the strength of native silk fibers. With the aim to improve the mechanical properties of silk fibers made from mini-spidroins and to understand the relationship between the protein design and the mechanical properties of the fibers, we designed 16 new spidroins, ranging from 31.7 to 59.5 kDa, that feature the globular spidroin N- and C-terminal domains, but harbor different repetitive sequences. We found that more than 50% of these constructs could be spun by extruding them into low-pH aqueous buffer and that the best fibers were produced from proteins whose repeat regions were derived from major ampullate spidroin 4 (MaSp4) and elastin. The mechanical properties differed between fiber types but did not correlate with the expected properties based on the origin of the repeats, suggesting that additional factors beyond protein design impact the properties of the fibers.

Assessing the performance of multi-InDel panels for human identification among admixed Brazilians

Insertion/deletion polymorphisms, or InDels, are widely present in the human genome. They have been considered as potential markers for forensic analysis because they can be genotyped using the CE platform and compatible typing techniques used in forensic laboratories. Additionally, InDels have lower mutation rates and often short amplicon sizes, making them ideal for detecting degraded samples. However, most InDels are bi-allelic; therefore, their discrimination power is relatively low. A new set of genetic marker called multi-InDels was reported to improve InDel's informativeness. Multi-InDel markers are generally designated as microhaplotypes encompassing two or more InDels within a short distance, usually less than 200bp. In this study, we evaluated the applicability of three previously proposed panels of multi-InDel markers, designed for Asian populations, for human identification in Brazil. We assessed all the multi-InDel markers using high-coverage whole-genome sequencing data from a census-based cohort of 1,171 Brazilians residing in São Paulo, the largest Brazilian capital. The results showed that most markers are informative for Brazilian individuals since they present more than three frequent haplotypes with different sizes. However, most markers are prone to amplification/sequencing errors due to repetitive or low-complexity regions. Among the tested panels, the one from Huang et al. (2014) is the most promising for forensic use in Brazil, with a combined match probability and cumulative power of exclusion of 4.92 ×10-14 and 0.9991, respectively. Nevertheless, these values are low compared to the ones obtained with CODIS STRs (short tandem repeats) and larger SNP (single nucleotide polymorphisms) panels. Therefore, new attempts to scan the human genome for highly polymorphic multi-InDel markers are still necessary to obtain a suitable panel of multi-InDels for worldwide populations.

Multi-omics analyzes of Rosa gigantea illuminate tea scent biosynthesis and release mechanisms.

Rose is an important ornamental crop cultivated globally for perfume production. However, our understanding of the mechanisms underlying scent production and molecular breeding for fragrance is hindered by the lack of a reference genome for tea roses. We present the first complete telomere-to-telomere (T2T) genome of Rosa gigantea, with high quality (QV > 60), including detailed characterization of the structural features of repetitive regions. The expansion of genes associated with phenylpropanoid biosynthesis may account for the unique tea scent. We uncover the release rhythm of aromatic volatile organic compounds and their gene regulatory networks through comparative genomics and time-ordered gene co-expression networks. Analyzes of eugenol homologs demonstrate how plants attract pollinators using specialized phenylpropanoids in specific tissues. This study highlights the conservation and utilization of genetic diversity from wild endangered species through multi-omics approaches, providing a scientific foundation for enhancing rose fragrance via de novo domestication.

Contrasting and combining transcriptome complexity captured by short and long RNA sequencing reads.

Mapping transcriptomic variations using either short- or long-reads RNA sequencing is a staple of genomic research. Long reads are able to capture entire isoforms and overcome repetitive regions, while short reads still provide improved coverage and error rates. Yet how to quantitatively compare the technologies, can we combine those, and what may be the benefit of such a combined view remain open questions. We tackle these questions by first creating a pipeline to assess matched long and short reads data using a variety of transcriptome statistics. We find that across datasets, algorithms, and technologies, matched short reads data detects roughly 30% more splice junctions such that 10-30% of the splice junctions included at 20% or more by short reads are missed by long reads. In contrast, long reads detect many more intron retention events and can detect full isoforms, pointing to the benefit of combining the technologies. We introduce MAJIQ-L, an extension of the MAJIQ software to enable a unified view of transcriptome variations from both technologies and demonstrate its benefits. Our software can be used to assess any future long-read technology or algorithm, and combine it with short reads data for improved transcriptome analysis.

A genome assembly and transcriptome atlas of the inbred Babraham pig to illuminate porcine immunogenetic variation.

The inbred Babraham pig serves as a valuable biomedical model for research due to its high level of homozygosity, including in the major histocompatibility complex (MHC) loci and likely other important immune-related gene complexes, which are generally highly diverse in outbred populations. As the ability to control for this diversity using inbred organisms is of great utility, we sought to improve this resource by generating a long-read whole genome assembly and transcriptome atlas of a Babraham pig. The genome was de novo assembled using PacBio longreads and error-corrected using Illumina shortreads. Assembled contigs were then mapped to the porcine reference assembly, Sscrofa11.1, to generate chromosome-level scaffolds. The resulting TPI_Babraham_pig_v1 assembly is nearly as contiguous as Sscrofa11.1 with a contig N50 of 34.95 Mb and contig L50 of 23. The remaining sequence gaps are generally the result of poor assembly across large and highly repetitive regions such as the centromeres and tandemly duplicated gene families, including immune-related gene complexes, that often vary in gene content between haplotypes. We also further confirm homozygosity across the Babraham MHC and characterize the allele content and tissue expression of several other immune-related gene complexes, including the antibody and T cell receptor loci, the natural killer complex, and the leukocyte receptor complex. The Babraham pig genome assembly provides an alternate highly contiguous porcine genome assembly as a resource for the livestock genomics community. The assembly will also aid biomedical and veterinary research that utilizes this animal model such as when controlling for genetic variation is critical.

High-quality haplotype-resolved chromosome assembly provides evolutionary insights and targeted steviol glycosides (SGs) biosynthesis in Stevia rebaudiana Bertoni.

Stevia rebaudiana Bertoni is popular source of plant-derived low/no-calorie natural sweeteners (LNCSs), collectively known as steviol glycosides (SGs). Nevertheless, genetic predisposition for targeted biosynthesis of SGs is complex due to multi-substrate functionality of key uridine diphosphate glycosyltransferases (UGTs). Here, we created a high-quality monoploid assembly of 1.34 Gb with N50 value of 110 Mb, 55 551 predicted protein-coding genes, and ~80% repetitive regions in Rebaudioside-A (Reb-A) enriched cultivar of S. rebaudiana. Additionally, a haplotype-based chromosome assembly consisting of haplotype A and haplotype B with an overall genome size of 2.33Gb was resolved, harbouring 639 634 variants including single nucleotide polymorphisms (SNPs), indels and structural variants (SVs). Furthermore, a lineage-specific whole genome duplication analysis revealed that gene families encoding UGTs and Cytochrome-P450 (CYPs) were tandemly duplicated. Additionally, expression analysis revealed five tandemly duplicated gene copies of UGT76G1 having significant correlations with Reb-A content, and identified key residue (leu200val) in the glycosylation of Reb-A. Furthermore, missense variations identified in the acceptor region of UGT76G1 in haplotype resolve genome, transcriptional and molecular docking analysis were confirmed with resequencing of 10 diverse stevia genotypes (~25X). Gene regulatory network analysis identified key transcription factors (MYB, bHLH, bZIP and AP2-ERF) as potential regulators of SG biosynthesis. Overall, this study provides haplotype-resolved chromosome-level genome assembly for genome editing and enhancing breeding efforts for targeted biosynthesis of SGs in S. rebaudiana.

Abstract A083: Genomic Analysis of Structural Variations in Pancreatic Cancer Using Long-Read Sequencing

Abstract Objective: Structural variations (SVs) constitute the greatest source of genomic alterations leading to the oncogenesis of many cancers, including the deadliest pancreatic cancer (PC). However, SVs in PC remain largely undefined due to technological limitations of the traditional short-read sequencing. This study aims to establish a comprehensive signature of genomic SVs in PC. Methods: PacBio whole genome long-read sequencing was employed to investigate the genomic landscape of SVs in eight tissues from four pancreatic cancer patients. A variety of SVs callers, including pbsv, Sniffles, cuteSV, and svim, were comprehensively adopted to improve the accuracy of SVs detection. Many undefined characteristics of germline and somatic SVs were revealed by comparing with multiple previously published databases. Besides, the impacts of structural variations on 3D chromatin organization were analyzed by integrating multi-omics data including Hi-C, RNA seq and ChIP seq. Results: A total of 26,844 and 27,028 non-redundant SVs were identified in human pancreatic cancer and matched para-cancerous tissues, respectively. Notably, among these SVs, 23.97% were novel and had not been previously reported. Germline SVs were further characterized and found enriched in 25 well-known susceptible genes, such as TP63, PVT1, and ABO. Additionally, we proposed a panel of germline SVs with predicted highest pathogenicity, involving STOX1, DSPP, and WRN. Totally, 616 somatic SVs were identified and presented high burdens in patients with lymph node metastasis. We observed that somatic DELs and INSs were significantly more prevalent in repetitive regions than in non-repetitive regions. Interestingly, DELs showed a decrease in the proportion occurring in simple repeat regions but an increase in the proportion occurring in LINE and SINE regions compared to INSs. Moreover, it was observed that deletions within topologically associated domains were associated with local enhanced interactions and disrupted chromatin loops, which might influence H3K27ac modification of histone contributing to enhancer or silencer hijacking. Conclusion: This study provides insights into the genomic signature of SVs in human pancreatic cancer. These findings might shed new light on the complexity of SVs and their pathogenesis by interplaying with chromatin organization. Citation Format: Yongxing Du, Xiaohao Zheng, Yunjie Duan, Chengfeng Wang. Genomic Analysis of Structural Variations in Pancreatic Cancer Using Long-Read Sequencing [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr A083.

Long-read DNA and cDNA sequencing identify cancer-predisposing deep intronic variation in tumor-suppressor genes.

The vast majority of deeply intronic genomic variants are benign, but some extremely rare or private deep intronic variants lead to exonification of intronic sequence with abnormal transcriptional consequences. Damaging variants of this class are likely underreported as causes of disease for several reasons: Most clinical DNA and RNA testing does not include full intronic sequences; many of these variants lie in complex repetitive regions that cannot be aligned from short-read whole-genome sequence; and, until recently, consequences of deep intronic variants were not accurately predicted by in silico tools. We evaluated the frequency and consequences of rare deep intronic variants for families severely affected with breast, ovarian, pancreatic, and/or metastatic prostate cancer, but with no causal variant identified by any previous genomic or cDNA-based approach. For 10 tumor-suppressor genes, we used multiplexed adaptive sampling long-read DNA sequencing and cDNA sequencing, based on patient-derived DNA and RNA, to systematically evaluate deep intronic variation. We identified all variants across the full genomic loci of targeted genes, applied the in silico tools SpliceAI and Pangolin to predict variants of functional consequence, and then carried out long-read cDNA sequencing to identify aberrant transcripts. For eight of the 120 (6%) previously unsolved families, rare deep intronic variants in BRCA1, PALB2, and ATM create intronic pseudoexons that are spliced into transcripts, leading to premature truncations. These results suggest that long-read DNA and cDNA sequencing can be integrated into variant discovery, with strategies for accurately characterizing pathogenic variants.