Repetitive Regions Research Articles

Pan-genome survey of Septoria pistaciarum, causal agent of Septoria leaf spot of pistachios, across three Aegean sub-regions of Greece.

Septoria pistaciarum, a causal agent of Septoria leaf spot disease of pistachio, is a fungal pathogen that causes substantial losses in the cultivation, worldwide. This study describes the first pan-genome-based survey of this phytopathogen-comprising a total of 27 isolates, with 9 isolates each from 3 regional units of Greece (Pieria, Larissa and Fthiotida). The reference isolate (SPF8) assembled into a total of 43.1 Mb, with 38.6% contained within AT-rich regions of approximately 37.5% G:C. The genomes of the 27 isolates exhibited on average 42% gene-coding and 20% repetitive regions. The genomes of isolates from the southern Fthiotida region appeared to more diverged from each other than the other regions based on SNP-derived trees, and also contained isolates similar to both the Pieria and Larissa regions. In contrast, isolates of the Pieria and Larissa were less diverse and distinct from one another. Asexual reproduction appeared to be typical, with no MAT1-2 locus detected in any isolate. Genome-based prediction of infection mode indicated hemibiotrophic and saprotrophic adaptations, consistent with its long latent phase. Gene prediction and orthology clustering generated a pan-genome-wide gene set of 21,174 loci. A total of 59 ortholog groups were predicted to contain candidate effector proteins, with 36 (61%) of these either having homologs to known effectors from other species or could be assigned predicted functions from matches to conserved domains. Overall, effector prediction suggests that S. pistaciarum employs a combination of defensive effectors with roles in suppression of host defenses, and offensive effectors with a range of cytotoxic activities. Some effector-like ortholog groups presented as divergent versions of the same protein, suggesting region-specific adaptations may have occurred. These findings provide insights and future research directions in uncovering the pathogenesis and population dynamics of S. pistaciarum toward the efficient management of Septoria leaf spot of pistachio.

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.

ULTRA-Effective Labeling of Repetitive Genomic Sequence.

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 released under an open license, and available for download at https://github.com/TravisWheelerLab/ULTRA.

Analyzing imbalance of short tandem repeats for pancreatic cancer detection.

e16359 Background: Short tandem repeats (STRs), alternatively known as microsatellites, encompass repeat units of 1 to 6 base pairs (bp) in the genome and function as regulators of gene expression, impacting plasticity and complex traits. STRs are prone to hypermutation with alterations correlated to pathogenicity in multiple Mendelian and acquired disorders. STR variant classes include insertions, mobile element insertions (MEIs), deletions, and multi-allelic copy number variants (mCNVs). These can lead to repeat expansions, allelic imbalance (AI), and microsatellite instability (MSI) observed in diseases such as Huntington's disease, hereditary ataxia, and multiple cancers. In pancreatic cancer, AI and associated loss-of-heterozygosity (LOH) at tumor suppressor loci flanked by hypervariable STR regions correspond to a pathogenic phenotype with a risk of aggressive disease. Consequently, it is critical to develop accurate and robust methods to precisely identify and genotype pancreatic samples with varying specimen quality in a clinical setting to aid in diagnosis. Methods: Capillary electrophoresis (CE) and Sanger sequencing have been used to analyze STRs. The availability of newer tools such as 2nd generation short-read (NGS) and 3rd generation long-read (TGS) sequencers could allow for high throughput scaling, however, informatics challenges associated with analyzing repetitive regions remain. Here we developed amplification and enrichment methods for targeted analysis for detection by CE, NGS and TGS. Results: Amplification and enrichment strategies for detecting 17 short tandem repeat regions that play a role in pancreatic carcinogenesis were developed. Methods were optimized for detecting STR alterations in cell-free nucleic acids isolated from endoscope-guided pancreatic fine needle aspirate biopsies. Furthermore, informatics tools were developed to analyze short-read and long-read sequencing data to accurately analyze repeat regions. Conclusions: Here we compared 3 platforms (CE, NGS, and TGS) and found that CE remains the gold standard for analyzing AI/LOH with data comparable to long-read TGS, while short-read NGS is not always amenable to accurate analysis dependent on the region of interest. Additionally, we found that artifacts of amplification persist, irrespective of the 3 platforms analyzed.

ACMGA: a reference-free multiple-genome alignment pipeline for plant species

BackgroundThe short-read whole-genome sequencing (WGS) approach has been widely applied to investigate the genomic variation in the natural populations of many plant species. With the rapid advancements in long-read sequencing and genome assembly technologies, high-quality genome sequences are available for a group of varieties for many plant species. These genome sequences are expected to help researchers comprehensively investigate any type of genomic variants that are missed by the WGS technology. However, multiple genome alignment (MGA) tools designed by the human genome research community might be unsuitable for plant genomes.ResultsTo fill this gap, we developed the AnchorWave-Cactus Multiple Genome Alignment (ACMGA) pipeline, which improved the alignment of repeat elements and could identify long (> 50 bp) deletions or insertions (INDELs). We conducted MGA using ACMGA and Cactus for 8 Arabidopsis (Arabidopsis thaliana) and 26 Maize (Zea mays) de novo assembled genome sequences and compared them with the previously published short-read variant calling results. MGA identified more single nucleotide variants (SNVs) and long INDELs than did previously published WGS variant callings. Additionally, ACMGA detected significantly more SNVs and long INDELs in repetitive regions and the whole genome than did Cactus. Compared with the results of Cactus, the results of ACMGA were more similar to the previously published variants called using short-read. These two MGA pipelines identified numerous multi-allelic variants that were missed by the WGS variant calling pipeline.ConclusionsAligning denovo assembled genome sequences could identify more SNVs and INDELs than mapping short-read. ACMGA combines the advantages of AnchorWave and Cactus and offers a practical solution for plant MGA by integrating global alignment, a 2-piece-affine-gap cost strategy, and the progressive MGA algorithm.

On Minimizers and Convolutional Filters: Theoretical Connections and Applications to Genome Analysis.

Minimizers and convolutional neural networks (CNNs) are two quite distinct popular techniques that have both been employed to analyze categorical biological sequences. At face value, the methods seem entirely dissimilar. Minimizers use min-wise hashing on a rolling window to extract a single important k-mer feature per window. CNNs start with a wide array of randomly initialized convolutional filters, paired with a pooling operation, and then multiple additional neural layers to learn both the filters themselves and how they can be used to classify the sequence. In this study, our main result is a careful mathematical analysis of hash function properties showing that for sequences over a categorical alphabet, random Gaussian initialization of convolutional filters with max-pooling is equivalent to choosing a minimizer ordering such that selected k-mers are (in Hamming distance) far from the k-mers within the sequence but close to other minimizers. In empirical experiments, we find that this property manifests as decreased density in repetitive regions, both in simulation and on real human telomeres. We additionally train from scratch a CNN embedding of synthetic short-reads from the SARS-CoV-2 genome into 3D Euclidean space that locally recapitulates the linear sequence distance of the read origins, a modest step toward building a deep learning assembler, although it is at present too slow to be practical. In total, this article provides a partial explanation for the effectiveness of CNNs in categorical sequence analysis.

Simultaneous profiling of chromatin accessibility and DNA methylation in complete plant genomes using long-read sequencing.

Epigenetic regulations, including chromatin accessibility, nucleosome positioningand DNA methylation intricately shape genome function. However, current chromatin profiling techniques relying on short-read sequencing technologies fail to characterise highly repetitive genomic regions and cannot detect multiple chromatin features simultaneously. Here, we performed Simultaneous Accessibility and DNA Methylation Sequencing (SAM-seq) of purified plant nuclei. Thanks to the use of long-read nanopore sequencing, SAM-seq enables high-resolution profiling of m6A-tagged chromatin accessibility together with endogenous cytosine methylation in plants. Analysis of naked genomic DNA revealed significant sequence preference biases of m6A-MTases, controllable through a normalisation step. By applying SAM-seq to Arabidopsis and maize nuclei we obtained fine-grained accessibility and DNA methylation landscapes genome-wide. We uncovered crosstalk between chromatin accessibility and DNA methylation within nucleosomes of genes, TEs, and centromeric repeats. SAM-seq also detects DNA footprints over cis-regulatory regions. Furthermore, using the single-molecule information provided by SAM-seq we identified extensive cellular heterogeneity at chromatin domains with antagonistic chromatin marks, suggesting that bivalency reflects cell-specific regulations. SAM-seq is a powerful approach to simultaneously study multiple epigenetic features over unique and repetitive sequences, opening new opportunities for the investigation of epigenetic mechanisms.

Comparative evaluation of SNVs, indels, and structural variations detected with short- and long-read sequencing data

Short- and long-read sequencing technologies are routinely used to detect DNA variants, including SNVs, indels, and structural variations (SVs). However, the differences in the quality and quantity of variants detected between short- and long-read data are not fully understood. In this study, we comprehensively evaluated the variant calling performance of short- and long-read-based SNV, indel, and SV detection algorithms (6 for SNVs, 12 for indels, and 13 for SVs) using a novel evaluation framework incorporating manual visual inspection. The results showed that indel-insertion calls greater than 10 bp were poorly detected by short-read-based detection algorithms compared to long-read-based algorithms; however, the recall and precision of SNV and indel-deletion detection were similar between short- and long-read data. The recall of SV detection with short-read-based algorithms was significantly lower in repetitive regions, especially for small- to intermediate-sized SVs, than that detected with long-read-based algorithms. In contrast, the recall and precision of SV detection in nonrepetitive regions were similar between short- and long-read data. These findings suggest the need for refined strategies, such as incorporating multiple variant detection algorithms, to generate a more complete set of variants using short-read data.

Phased nanopore assembly with Shasta and modular graph phasing with GFAse.

Reference-free genome phasing is vital for understanding allele inheritance and the impact of single-molecule DNA variation on phenotypes. To achieve thorough phasing across homozygous or repetitive regions of the genome, long-read sequencing technologies are often used to perform phased de novo assembly. As a step toward reducing the cost and complexity of this type of analysis, we describe new methods for accurately phasing Oxford Nanopore Technologies (ONT) sequence data with the Shasta genome assembler and a modular tool for extending phasing to the chromosome scale called GFAse. We test using new variants of ONT PromethION sequencing, including those using proximity ligation, and show that newer, higher accuracy ONT reads substantially improve assembly quality.

A data-adaptive methods in detecting exogenous methyltransferase accessible chromatin in human genome using nanopore sequencing.

Identifying chromatin accessibility is one of the key steps in studying the regulation of eukaryotic genomes. The combination of exogenous methyltransferase and nanopore sequencing provides an strategy to identify open chromatin over long genomic ranges at the single-molecule scale. However, endogenous methylation, non-open-chromatin-specific exogenous methylation and base-calling errors limit the accuracy and hinders its application to complex genomes. We systematically evaluated the impact of these three influence factors, and developed a model-based computational method, methyltransferase accessible genome region finder (MAGNIFIER), to address the issues. By incorporating control data, MAGNIFIER attenuates the three influence factors with data-adaptive comparison strategy. We demonstrate that MAGNIFIER is not only sensitive to identify the open chromatin with much improved accuracy, but also able to detect the chromatin accessibility of repetitive regions that are missed by NGS-based methods. By incorporating long-read RNA-seq data, we revealed the association between the accessible Alu elements and non-classic gene isoforms. Freely available on web at https://github.com/Goatofmountain/MAGNIFIER.

A phased genome of the highly heterozygous 'Texas' almond uncovers patterns of allele-specific expression linked to heterozygous structural variants.

The vast majority of traditional almond varieties are self-incompatible, and the level of variability of the species is very high, resulting in a high-heterozygosity genome. Therefore, information on the different haplotypes is particularly relevant to understand the genetic basis of trait variability in this species. However, although reference genomes for several almond varieties exist, none of them is phased and has genome information at the haplotype level. Here, we present a phased assembly of genome of the almond cv. Texas. This new assembly has 13% more assembled sequence than the previous version of the Texas genome and has an increased contiguity, in particular in repetitive regions such as the centromeres. Our analysis shows that the 'Texas' genome has a high degree of heterozygosity, both at SNPs, short indels, and structural variants level. Many of the SVs are the result of heterozygous transposable element insertions, and in many cases, they also contain genic sequences. In addition to the direct consequences of this genic variability on the presence/absence of genes, our results show that variants located close to genes are often associated with allele-specific gene expression, which highlights the importance of heterozygous SVs in almond.

Modulating Polyalanine Motifs of Synthetic Spidroin for Controllable Preassembly and Strong Fiber Formation.

Spider dragline (major ampullate) silk is one of the toughest known fibers in nature and exhibits an excellent combination of high tensile strength and elasticity. Increasing evidence has indicated that preassembly plays a crucial role in facilitating the proper assembly of silk fibers by bridging the mesoscale gap between spidroin molecules and the final strong fibers. However, it remains challenging to control the preassembly of spidroins and investigate its influence on fiber structural and mechanical properties. In this study, we explored to bridge this gap by modulating the polyalanine (polyA) motifs in repetitive region of spidroins to tune their preassemblies in aqueous dope solutions. Three biomimetic silk proteins with varying numbers of alanine residues in polyA motif and comparable molecular weights were designed and biosynthesized, termed as N16C-5A, N15C-8A, and N13C-12A, respectively. It was found that all three proteins could form nanofibril assemblies in the concentrated aqueous dopes, but the size and structural stability of the fibrils were distinct from each other. The silk protein N15C-8A with 8 alanine residues in polyA motif allowed for the formation of stable nanofibril assemblies with a length of approximately 200 nm, which were not prone to disassemble or aggregate as that of N16C-5A and N13C-12A. More interestingly, the stable fibril assembly of N15C-8A enabled spinning of simultaneously strong (623.3 MPa) and tough (107.1 MJ m-3) synthetic fibers with fine molecular orientation and close interface packing of fibril bundles. This work highlights that modulation of polyA motifs is a feasible way to tune the morphology and stability of the spidroin preassemblies in dope solutions, thus controlling the structural and mechanical properties of the resulting fibers.

Phased assembly of neo-sex chromosomes reveals extensive Y degeneration and rapid genome evolution in Rumex hastatulus.

Y chromosomes are thought to undergo progressive degeneration due to stepwise loss of recombination and subsequent reduction in selection efficiency. However, the timescales and evolutionary forces driving degeneration remain unclear. To investigate the evolution of sex chromosomes on multiple timescales, we generated a high-quality phased genome assembly of the massive older (<10MYA) and neo (<200,000 years) sex chromosomes in the XYY cytotype of the dioecious plant Rumex hastatulus and a hermaphroditic outgroup R. salicifolius. Our assemblies, supported by fluorescence in situ hybridization, confirmed that the neo-sex chromosomes were formed by two key events: an X-autosome fusion and a reciprocal translocation between the homologous autosome and the Y chromosome. The enormous sex-linked regions of the X (296 MB) and two Y chromosomes (503 MB) both evolved from large repeat-rich genomic regions with low recombination; however, the complete loss of recombination on the Y still led to over 30% gene loss and major rearrangements. In the older sex-linked region, there has been a significant increase in transposable element abundance, even into and near genes. In the neo sex-linked regions, we observed evidence of extensive rearrangements without gene degeneration and loss. Overall, we inferred significant degeneration during the first 10 million years of Y chromosome evolution but not on very short timescales. Our results indicate that even when sex chromosomes emerge from repetitive regions of already-low recombination, the complete loss of recombination on the Y chromosome still leads to a substantial increase in repetitive element content and gene degeneration.

Remarkably High Repeat Content in the Genomes of Sparrows: The Importance of Genome Assembly Completeness for Transposable Element Discovery.

Transposable elements (TE) play critical roles in shaping genome evolution. Highly repetitive TE sequences are also a major source of assembly gaps making it difficult to fully understand the impact of these elements on host genomes. The increased capacity of long-read sequencing technologies to span highly repetitive regions promises to provide new insights into patterns of TE activity across diverse taxa. Here we report the generation of highly contiguous reference genomes using PacBio long-read and Omni-C technologies for three species of Passerellidae sparrow. We compared these assemblies to three chromosome-level sparrow assemblies and nine other sparrow assemblies generated using a variety of short- and long-read technologies. All long-read based assemblies were longer (range: 1.12 to 1.41 Gb) than short-read assemblies (0.91 to 1.08 Gb) and assembly length was strongly correlated with the amount of repeat content. Repeat content for Bell's sparrow (31.2% of genome) was the highest level ever reported within the order Passeriformes, which comprises over half of avian diversity. The highest levels of repeat content (79.2% to 93.7%) were found on the W chromosome relative to other regions of the genome. Finally, we show that proliferation of different TE classes varied even among species with similar levels of repeat content. These patterns support a dynamic model of TE expansion and contraction even in a clade where TEs were once thought to be fairly depauperate and static. Our work highlights how the resolution of difficult-to-assemble regions of the genome with new sequencing technologies promises to transform our understanding of avian genome evolution.

First Trials of Genome Analyses in Some Onobrychis Species using Dot-Blot and Genomic in situ Hybridization Techniques

The origin and genome composition of tetraploid cultivated Onobrychis viciifolia (2n = 4x = 28) were analyzed using dot-blot and genomic in situ hybridization (GISH) techniques. Dot-blot hybridization was used to find a genomic affinity between O. viciifolia and 16 diploid Onobrychis species. The hypothesis on the origin of the O. viciifolia was tested using GISH. Dot-blot analyses suggested a genomic affinity between O. viciifolia and four diploid Onobrychis species (O. kachetica, O. supina, O. pallasii, and O. vaginalis). Hybridization signals were observed on O. viciifolia chromosomes when gDNA of O. kachetica, O. supina, O. pallasi, and O. hypargyrea were used as probes. However, the observed chromosomal distribution of hybridization signals did not resemble GISH results. The observed signals colocalized with 35S rDNA or dispearse signals on all chromosomes were observed depending on the probe. Further investigations using more comprehensive and comparative analysis with both coding and repetitive DNA regions may provide a better understanding of the genome composition and evolution of O. viciifolia.

Abstract 2934: Somatic variant workflow with HiFi sequencing provides new insights in highly challenging cancer cases

Abstract Tumor evolution is a highly heterogeneous process where multiple oncogenic pathways can lead to host defense evasion. Advancements in genome sequencing are allowing us to better understand these processes and their impact. However, critical genomic variations that could be pivotal to the development of tumors may have remained undetected due to technological constraints of short-read sequencing. PacBio HiFi sequencing generates accurate (&amp;gt;99.9%) long reads (&amp;gt;15 kb) with native 5-methylcytosine information that can comprehensively delineate many variations, including ones which were previously inaccessible with short-read sequencing. Unlike standard whole-genome analysis, cancer variant calling must account for somatic variation, where the assumptions of a diploid genome are violated. We have developed and optimized a bioinformatics workflow for somatic variant detection with HiFi sequence data. To validate this pipeline, we sequenced two well-studied cancer cell lines (COLO829, HCC1395) to 60-fold depth and their matched normal lymphoblast cells (40-fold to 60-fold depth) and called all classes of variations (SNVs, INDELS, and structural variants). Next, we compared our calls against the Valle-Inclan (structural variants) and SEQC2 (small variants: SNV/INDEL) datasets. We achieved 92% F1 score for small variants across all variant allele frequencies (VAF) in the HCC1395 experiment. We observed a maintained accuracy (F1=91%) even at lower variant frequencies (10-20), highlighting the ability of HiFi sequencing to detect subclonal mutations. The workflow calls structural variants with high sensitivity, capturing 57/62 (92%) of all previously validated SVs in COLO829 at all VAF. Lastly, we applied our pipeline to five diverse tumor samples that exhibit complex oncogenic phenotypes including homologous recombination deficiency (HRD) and high genomic instability, e.g. unresolved rearrangement breakpoints in repetitive regions and unknown oncogenic drivers when prior sequencing efforts did not provide full clarity as to the molecular drivers of tumorigenesis. Notably, we were able to identify and phase 5mC methylation of promoters together with large-scale structural variants in cancer genes involved in HRD. Taken together, we demonstrated the high accuracy of HiFi reads in resolving somatic variants and its potential to provide novel insights in complex cancer samples. The ability for long reads to resolve complex genomics aberrations and epigenetic markers that underly the tumorigenesis process will become indispensable in the realm of precision oncology. Citation Format: Khi Pin Chua, Ian McLaughlin, Oliver Hofmann, Kym Pham Stewart, Primo Baybayan, Jonathan Bibliowicz, Sean Grimmond, Zev Kronenberg, Michael A. Eberle. Somatic variant workflow with HiFi sequencing provides new insights in highly challenging cancer cases [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2934.

Abstract 3009: ATRX loss blocks the differentiation of mesenchymal stem cells and promotes undifferentiated sarcoma development

Abstract Soft tissue sarcomas (STSs) are a collection of rare tumor types originated from the mesenchymal tissues. Among the over 70 histological subtypes of STS, undifferentiated sarcoma (US), which lacks any discernible morphological features of differentiated tissues, accounts for over 20% of all STSs and is correlated with high tumor grade and poor prognosis. Recent genomic profiling in US has identified p53 and ATRX among the most frequently mutated or deleted genes. ATRX is a SWI/SNF2 type of chromatin remodeling factor which functions in a histone variant H3.3-specific chaperone complex to orchestrates replication-independent nucleosome assembly at repetitive heterochromatic DNA regions including telomeres. Loss-of-function mutations occur frequently in many tumor types and is associated with the development of alternative lengthening of telomere (ALT). However, how loss of ATRX function may contribute to tumorigenesis is largely unknown. Here, we demonstrated that ATRX is required for the terminal differentiation of mouse mesenchymal stem cells (MSCs) into multiple lineages, such as adipocytes and osteocytes. Targeted deletion of Atrx in mouse MSCs, but not terminally differentiated mesenchymal lineage cells, accelerated sarcoma initiation induced by loss of p53 and significantly shortened the overall survival. Atrx-deficient tumors express high level of MSC markers such as CD44 and CD29 and exhibit pathological features highly reminiscent of human high-grade US. Transcriptomic analysis indicates that Atrx deficiency is associated with enhanced proliferation. Together, our data indicates that ATRX deficiency contributes to undifferentiated sarcoma development by inhibiting mesenchymal stem cell differentiation. Citation Format: Yiming Cai, Jun Yao, Dean N. Pan, Yanqiang Jin, James M. You, Wantong Yao, Haoqiang Ying. ATRX loss blocks the differentiation of mesenchymal stem cells and promotes undifferentiated sarcoma development [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 3009.

Abstract 6250: The RNA editing landscape of lung cancer in never smokers

Abstract Adenosine-to-Inosine (A-to-I) editing represents a crucial RNA modification mechanism, holding the potential to drive carcinogenesis. This sophisticated post-transcriptional process is catalyzed by a series of ADAR (adenosine deaminase acting on RNA) family members, which can profoundly reshape the cellular epitranscriptomic landscape. While previous explorations have illuminated the important role of A-to-I editing in lung cancer tumorigenesis and prognosis, most studies have focused on lung cancer from smokers. To investigate the contribution on RNA-editing in lung cancers in never smokers (LCINS) , we embarked on a rigorous dissection of A-to-I RNA editing events in 603 LCINS. Harnessing transcriptome and whole-genome sequencing technologies, we identified 15,880 A-to-I sites, of which 75% were positively linked to the enzymatic activity of ADAR1. 92.80% of detected editing sites were located at Alu repetitive regions, with the remainder in non_Alu repeat (4.1%) and non-repeat regions (3.1%). The global RNA editing levels, measured as Alu Editing Index (AEI), were found to be significantly associated with ADAR1 expression, Tumor Mutational Burden, and Neoantigens Burden. A subtle correlation between global RNA editing levels and tumor stage was also noted. Delving into cancer-associated editing events, we identified 5,539 differentially edited sites in tumors compared with normal tissues, which were located at 823 genes, including several key tumor suppressors and oncogenes, like MDM2, BRAF, TP53, BRCA2, ATM, and VHL. Subsequent pathway analysis identified TGF-beta, Notch Signaling, and DNA Damage Response as the key pathways for cancer progression. Using the characterized A-to-I editing profiles, we built a prognostic risk stratification model, with high risk scores significantly linked to poor survival outcomes, even after adjusting for other clinical factors. Our study provides a comprehensive A-to-I editing landscape of lung cancer in never smokers, highlighting the potential roles of RNA modifications in the pathogenesis of this lethal disease. Citation Format: Jian Sang, Wei Zhao, Tongwu Zhang, Maria Teresa Landi. The RNA editing landscape of lung cancer in never smokers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6250.

Abstract 405: Translocation detection in cancer using low-pass pore-c sequencing

Abstract Complex chromosomal rearrangements, including translocations, play a critical role in oncogenesis and are often identified as recurrent genetic aberrations in hematologic malignancies and solid tumors[1]. Translocation detection by karyotyping of an individual’s metaphase chromosomes remains challenging for detection of balanced rearrangements, which have no gain or loss of genetic material. Rearrangement detection using whole-genome sequencing is a viable alternative, but it relies on breakpoint-spanning reads and requires high sequencing depth (30-60x) with long reads to achieve high sensitivity, especially in repetitive regions of the genome[2]. Here, we describe a workflow for translocation detection at low sequencing depth with Oxford Nanopore’s long read chromatin conformation capture technique, Pore-C[3]. Importantly, for translocation calling, Pore-C does not rely on breakpoint-spanning reads but rather the high intrachromosomal interaction frequency of genomic regions around the breakpoint, thus largely lowering sequencing depth requirements and reducing mapping issues in low complexity regions. We prepared, barcoded, and sequenced Pore-C libraries of 3 cancer cell lines including lung cancer (A549), Acute Monocytic Leukemia (THP-1), melanoma (COLO 829) and its matching normal (COLO 829 BL) on a single Q20+ MinION flow cell (FLO-MIN114). Genome-wide contact maps of low-pass data (&amp;lt;1.5 Gbps per sample) were compared against higher depth (&amp;gt;30 Gbps per sample) Hi-C maps [4], revealing that low-pass Pore-C successfully captured large-scale genomic rearrangement. For example, chromosomal pairs chr8-chr11 and chr15-chr19 in A549, chr9-chr11 and chr1-chr20 in THP1, and chr7-chr15 in Colo829 were detected at &amp;lt;0.5X depth of sequencing coverage. These translocation events were further validated by breakpoint analysis using adaptive sampling, where targeted regions were previously confirmed by independent studies[4],[5]. Low-pass Pore-C detects translocations in an unbiased manner and does not require prior knowledge of the translocation structure. Combined with its simple sample-preparation workflow and the capability to provide genome-wide copy-number information in a single experiment, it can serve as a cost-effective and comprehensive tool for cancer genomic studies. [1] Chromosomal translocations in human cancer, Nature, 372, 143 (1994) [2] Hi-C as a tool for precise detection and characterisation of chromosomal rearrangements and copy number variation in human tumors, Genome Biology, 18, 125 (2017) [3] Identifying synergistic high-order 3D chromatin conformations from genome-scale nanopore concatemer sequencing, Nature Biotechnology, 40, 1488(2022) [4] Chromosomal translocations detection in cancer cells using chromosomal conformation capture data, Genes (Basel), 13, 7 (2022) [5] A multi-platform reference for somatic structural variation detection, Cell Genomics, 2, 6 (2022) Citation Format: Scott Hickey, Xiaoguang Dai, Sergey Aganezov, John Beaulaurier, Eoghan Harrington, Sissel Juul. Translocation detection in cancer using low-pass pore-c sequencing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 405.

Abstract 2443: Improved detection of low frequency mutations in ovarian and endometrial cancers by utilizing a highly accurate sequencing platform

Abstract Ovarian and endometrial cancers come within the top-4 for incident cancers as well as deaths in North American women. Cure rates have not improved in 30 years as high-grade subtypes continue to be diagnosed in Stage III/IV. Attempts at early diagnosis have failed because high-grade cancer cells exfoliate and metastasize while the primary cancer is small and undetectable by existing tests based on imaging and blood-based tumor markers. DOvEEgene (Detecting Ovarian and Endometrial cancers Early using genomics) is a genomic uterine pap test developed by a McGill team to screen and detect these cancers while they are confined to the gynecologic organs and curable by surgery. The test identifies pathogenic somatic mutations in uterine brush samples. Here we tested the Onso system, a highly accurate sequencing technology from PacBio in order to potentially increase sensitivity while driving down sequencing costs by reducing required sequencing depth vs the current NGS standard. A highly sensitive, error-correcting capture technology (DOvEEgene-SureSelectHS) utilizing duplex error correction sequencing interrogated the exons of 23 genes involved in the development of sporadic and hereditary ovarian and endometrial cancers. We applied a combination of germline gene panel testing on saliva samples with deep duplex sequencing to detect somatic mutations at &amp;lt;0.1% VAF, interrogation of microsatellite loci for instability, and low coverage WGS for copy number analysis of uterine brush samples. We sequenced 20 duplex Illumina sequencing libraries produced using the DovEE assay at PE 100bp mode and compared Onso data in non- duplex sequencing mode as well as duplex sequencing mode to the original Illumina duplex sequencing method. Here, we present this comparison and highlight the benefits of high accuracy sequencing for the detection of very low frequency (&amp;lt;0.1%) somatic mutations. We observed improved mismatch rates for Onso data compared to Illumina, even after duplex error correction was applied. In addition, we found that more individuals are called as displaying microsatellite instablity from the Onso data, which may be due to improved sequencing performance in repetitive regions for Onso. Finally, we observed fewer potential false positive variant calls in the Onso data, highlighting the value of improved sequencing accuracy for rare variant detection. Citation Format: Timothée Revil, Nairi Pezeshkian, Lucy Gilbert, Alexandra Sockell, Jiannis Ragoussis. Improved detection of low frequency mutations in ovarian and endometrial cancers by utilizing a highly accurate sequencing platform [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2443.