Single Read Research Articles

Genetic and Microenvironment Features Do Not Distinguish Follicular Lymphoma Patients Requiring Immediate or Deferred Treatment.

Genetic and Microenvironment Features Do Not Distinguish Follicular Lymphoma Patients Requiring Immediate or Deferred Treatment.

Regulatory Role of microRNA of Milk Exosomes in Mastitis of Dairy Cows

The aim of this study was to compare the cargos of miRNA in exosomes isolated from the milk of healthy (H) cows, cows at risk of mastitis (ARM), and cows with subclinical mastitis (SCM). Based on the number of somatic cells and the percentage of polymorphonuclear cells, 10 cows were assigned to group H, 11 to group ARM, and 11 to group SCM. After isolating exosomes in milk by isoelectric precipitation and ultracentrifugation, the extracted RNA was sequenced to 50 bp long single reads, and these were mapped against Btau_5.0.1. The resulting 225 miRNAs were uploaded to the miRNet suite, and target genes for Bos taurus were identified based on the miRTarBase and miRanda databases. The list of differentially expressed target genes resulting from the comparisons of the three groups was enriched using the Function Explorer of the Kyoto Encyclopedia of Genes and Genomes. A total of 38, 18, and 12 miRNAs were differentially expressed (DE, p < 0.05) in the comparisons of H vs. ARM, ARM vs. SCM, and H vs. SCM, respectively. Only 1 DE miRNA was shared among the three groups (bta-mir-221), 1 DE miRNA in the H vs. SCM comparison, 9 DE miRNAs in the ARM vs. SCM comparison, and 21 DE miRNAs in the H vs. ARM comparison. A comparison of the enriched pathways of target genes from the H, SCM, and ARM samples showed that 19 pathways were differentially expressed in the three groups, while 56 were expressed in the H vs. SCM comparison and 57 in the H vs. ARM comparison. Analyzing milk exosome miRNA cargos can be considered as a promising approach to study the complex molecular machinery set in motion in response to mastitis in dairy cows.

Nanopores as versatile single-molecule tools: From DNA turbines to protein sequencing.

Nanopores offer ample opportunities for studying single biomolecules. I will present some recent examples of nanopore research from my lab: (1) DNA origami turbines powered by nanoscale flow. We demonstrated driven rotary motion of a nanoscale DNA origami turbine which harnesses energy from a water/ion flow generated by a static chemical or electrical potential gradient in a solid-state nanopore. Sustained unidirectional rotary motion of up to 20 revolutions/s were observed. These artificial nano-engines operate autonomously in physiological conditions, converting energy into useful mechanical work. (2) Nanopore-based sequential reading of peptides. We demonstrated a nanopore-based single-molecule peptide reader capable of reliably detecting single amino-acid substitutions within individual peptides. A peptide is linked to a DNA molecule and sequentially pulled through a biological nanopore by a DNA helicase in single amino-acid steps. Stepping ion-current signals enable discrimination of single-amino-acid substitutions in single reads. Notably, we demonstrated the capability to ‘rewind’ peptide reads, obtaining indefinitely many independent reads of the same molecule, yielding an undetectably low read errors. Recently, we expanded this concept to discriminating single post-translational modifications within peptides of mixed charge. These proof-of-concept experiments constitute a promising basis for the development of a single-molecule protein sequencer.

Development of a Novel Ulcerative Colitis Endoscopic Mayo Score Prediction Model Using Machine Learning.

Endoscopic assessment is a co-primary end point in inflammatory bowel disease registration trials, yet it is subject to inter- and intraobserver variability. We present an original machine learning approach to Endoscopic Mayo Score (eMS) prediction in ulcerative colitis and report the model's performance in differentiating key levels of endoscopic disease activity on full-length procedure videos. Seven hundred ninety-three full-length videos with centrally-read eMS were obtained from 249 patients with ulcerative colitis, who participated in a phase II trial evaluating mirikizumab (NCT02589665). A video annotation approach was established to extract mucosal features and associated eMS classification labels from each video to be used as inputs for model training. The primary objective of the model was a categorical prediction of inactive vs active endoscopic disease evaluated against 2 independent test sets: a full set with a baseline single human expert read and a consensus subset in which 2 human reads agreed. On the full test set of 147 videos, the model predicted inactive vs active endoscopic disease via the eMS with an area under the curve of 89%, accuracy of 84%, positive predictive value of 80%, and negative predictive value of 85%. In the consensus test set of 94 videos, the model predicted inactive vs active endoscopic disease with an area under the curve of 92%, accuracy of 89%, positive predictive value of 87%, and negative predictive value of 90%. We have demonstrated that this machine learning model supervised by mucosal features and eMS video annotations accurately differentiates key levels of endoscopic disease activity.

Assembly and Annotation of Viral Metagenomes from Short-Read Sequencing Data.

Viral metagenomics enables the detection, characterization, and quantification of viral sequences present in shotgun-sequenced datasets of purified virus-like particles and whole metagenomes. Next generation sequencing (Illumina) derived short single or paired-end read runs are a principal platform for metagenomics, and assembly of short reads allows for the identification of distinguishing viral signatures and complex genomic features for taxonomy and functional annotation. Here we describe the identification and characterization of viral genome sequences, bacteriophages, and eukaryotic viruses, from a cohort of human stool samples, using multiple methods. Following the purification of virus-like particles, sequencing, quality refinement, and genome assembly, we begin the protocol with raw short reads deposited in an open-source nucleotide archive. We highlight the use of VIBRANT, an automated computational tool for the characterization of microbial viruses and their viral community function. Finally, we also describe an alternative assembly-free option of mapping reads to established databases of reference genomes and previously characterized metagenome-assembled viral genomes.

On the Positional Single Error Correction and Double Error Detection in Racetrack Memories

In the era of non-volatile memories, the racetrack memory is a promising technology to pack hundreds of bits in a magnetic nanowire. A solid-state read head is grown alongside the nanowire to sense individual bits which are pushed across the head by a shifting force. However, the probabilistic nature of this shifting movement inflicts positional errors. Therefore, robust and low-cost error correcting codes are essential for a reliable alternative in on-chip memories and storage applications. Recent works focus on Varshamov-Tenengolts (VT) codes which can correct all single bit insertions and deletions. However, VT codes are incapable of detecting multiple deletions/insertions. Because a positional error corrupts multiple data words, multi-bit positional error detection is critical for racetrack memories. In this article, we propose a novel positional single error correction and double error detection (P-SECDED) code in the context of racetrack memories with a single read head. In particular, we adopt a postamble-based approach where a VT-encoded codeword appends a carefully selected bit-pattern, stored on the racetrack. We rigorously analyze the limitations of the postamble method, and deduce a criterion for postamble selection. We further provide a methodology to optimize this postamble selection in order to correct all single-bit errors and as much of two-bit errors as possible. Finally, we prove that all incurable two-bit errors are successfully detected. To the best of our knowledge, this work is the first attempt to provide P-SECDED fault-tolerance to three-dimensional racetrack memories which cannot afford multiple read heads.

Data and Computation Reuse in CNNs Using Memristor TCAMs

Exploiting computational and data reuse in CNNs is crucial for the successful design of resource-constrained platforms. In image recognition applications, high levels of input locality and redundancy present in CNNs have become the golden goose for skipping costly arithmetic operations. One promising technique for this consists in storing function responses of some input patterns into offline lookup tables and replacing online computation with search operations, which are highly efficient when implemented by emerging non-volatile memory technologies. In this work, we rethink both algorithm and architecture for exploiting locality and reuse opportunities by replacing entire convolutions with searches on Content-addressable Memories. By previously calculating convolution results and building compact lookup tables with our novel clustering algorithm, one can evaluate activations at constant time complexity, also requiring a single read operation of the current input tensor. Then, we devise a reconfigurable array of processing elements based on memristive Ternary Content-addressable Memories to efficiently implement the algorithmic solution and meet the flexibility requirements of several CNN architectures. Results show that our design reduces the number of multiplications and memory accesses proportionally to the number of convolutional layer channels. The average performance is 1,172 and 82 FPS for AlexNet and VGG-16 models, thus outperforming state-of-the-art works by 13×.

Single-read tRNA-seq analysis reveals coordination of tRNA modification and aminoacylation and fragmentation.

Transfer RNA (tRNA) utilizes multiple properties of abundance, modification, and aminoacylation in translational regulation. These properties were typically studied one-by-one; however, recent advance in high throughput tRNA sequencing enables their simultaneous assessment in the same sequencing data. How these properties are coordinated at the transcriptome level is an open question. Here, we develop a single-read tRNA analysis pipeline that takes advantage of the pseudo single-molecule nature of tRNA sequencing in NGS libraries. tRNAs are short enough that a single NGS read can represent one tRNA molecule, and can simultaneously report on the status of multiple modifications, aminoacylation, and fragmentation of each molecule. We find correlations among modification-modification, modification-aminoacylationand modification-fragmentation. We identify interdependencies among one of the most common tRNA modifications, m1A58, as coordinators of tissue-specific gene expression. Our method, SingLe-read Analysis of Crosstalks (SLAC), reveals tRNAome-wide networks of modifications, aminoacylation, and fragmentation. We observe changes of these networks under different stresses, and assign a function for tRNA modification in translational regulation and fragment biogenesis. SLAC leverages the richness of the tRNA-seq data and provides new insights on the coordination of tRNA properties.

VirPool: model-based estimation of SARS-CoV-2 variant proportions in wastewater samples

BackgroundThe genomes of SARS-CoV-2 are classified into variants, some of which are monitored as variants of concern (e.g. the Delta variant B.1.617.2 or Omicron variant B.1.1.529). Proportions of these variants circulating in a human population are typically estimated by large-scale sequencing of individual patient samples. Sequencing a mixture of SARS-CoV-2 RNA molecules from wastewater provides a cost-effective alternative, but requires methods for estimating variant proportions in a mixed sample.ResultsWe propose a new method based on a probabilistic model of sequencing reads, capturing sequence diversity present within individual variants, as well as sequencing errors. The algorithm is implemented in an open source Python program called VirPool. We evaluate the accuracy of VirPool on several simulated and real sequencing data sets from both Illumina and nanopore sequencing platforms, including wastewater samples from Austria and France monitoring the onset of the Alpha variant.ConclusionsVirPool is a versatile tool for wastewater and other mixed-sample analysis that can handle both short- and long-read sequencing data. Our approach does not require pre-selection of characteristic mutations for variant profiles, it is able to use the entire length of reads instead of just the most informative positions, and can also capture haplotype dependencies within a single read.

LCHC-DFT: A Low-Cost High-Coverage Design-for-Testability Technique to Detect Hard-to-Detect Faults in STT-MRAMs in the Presence of Process Variations

This paper proposes a low-cost yet high-coverage design-for-testability (DFT) scheme for improving the detection of hard-to-detect (HtD) faults in STT-MRAMs. It is based on introducing a voltage mismatch in the sense amplifier (SA). This mismatch along with the defects in the cell may bias the SA, leading to an incorrect read output which in turn make the HtD faults detectable. The efficacy of the proposed scheme is evaluated by calculating its detection capability in the presence of resistive defects. Evaluation results obtained for a 20nm STT-MRAM memory design show that the proposed scheme provides HtD fault coverage of 81.8% and 86.5%, on average, for intra-cell and inter-cell defects, respectively, with a negligible area overhead (1.1% for a 2Kbit array). In comparison with conventional March tests, which only detect easy-to-detect (EtD) faults, the proposed DFT technique covers both HtD and EtD faults with a faster approach, namely by using a single read operation. Furthermore, to guarantee that the cells affected by HtD faults trigger an incorrect read output under process variation (PV), a timing strategy based on modifying the control unit of the proposed DFT is suggested. The strategy controls the stress introduced by the DFT unit by altering the timing of DFT control signals. The timing alteration enables the detection of HtD faults in the devices with higher deviations from the nominal one due to PV, avoiding yield loss or test escapes.

Role of TNFRSF17 and GPRC5D Structural and Point Mutations in Resistance to Targeted Immunotherapies in Multiple Myeloma (MM)

Adaptive T cell therapy using chimeric antigen receptor (CAR) T cells and T cell engagers (TCE) targeting BCMA and GPRC5D have demonstrated very encouraging responses in heavily pre-treated multiple myeloma (MM). Recent studies interrogating T cells repertoires and fitness correlated resistance to these immune based therapies with exhausted T cell states. While in lymphoma, antigen escape with CD19 loss is observed in up to 30% of patients with acquired resistance to adaptive therapies, in MM TNFRSF17 or GPRC5D structural mutations are thought to be less prevalent in recipients of BCMA or GPRC5D-targeting CARs or TCEs . Bi-allelic loss (n=2) and a missense truncating mutation (n=1) of TNFRSF17 with CAR T cells, as well as one case of biallelic loss in TNFRSF17 with TCE are reported to date with no reported cases of bi-allelic loss of GPRC5D. Further studies of the role TNFRSF17 or GPRC5D structural or point mutations to the immune escape to these adaptive therapies are needed. Serial BM aspirates were collected from patients treated with BCMA or GPRC5D-targeting TCE or CARs prior to therapy and at relapse. MM cells were profiled with single cell mRNA (scRNAseq), single cell copy number (scCNVseq) using the 10x Genomics GemCode system and whole genome sequencing (WGS). Sequenced reads were aligned to hg38. Single cell reads were processed with CellRanger and downstream analyses with Seurat R package. In order to define the prevalence of TNFRSF17 or GRPC5D structural variants and mutations in MM, we performed WGS (n=19, 14 pre-CAR/TCE, 5 post-CAR/TCE) as well as scCNVseq (n=33, 16 RRMM, 7 pre-CAR/TCE, 8 post-CAR/TCE) on sorted CD138+ cells from relapsed MM patients. WGS (100x coverage) identified at baseline a subclonal deletion at the TNFRSF17 gene locus in only 1 patient; this small subclone subsequently drove the progression post BCMA CAR T cell therapy with an acquired biallelic loss of TNFRSF17. Mono-allelic large and focal deletions of GPRC5D (chr.12p) were detected by WGS in 7 cases (5 deletions, 2 copy neutral LOH). scCNVseq studies identified more frequent subclonal monoallelic copy number losses of TNFRSF17 in 11.2% of the cells (27884 MM cells) prior to anti-BCMA therapy exposure with the deletions ranging from 200 kb to 2.3 Mb. A homozygous deletion of TNFRSF17 was noted in 2 patients at the time of disease progression, one post CAR T and the other post BCMAxCD3 TCE. Structural mutations at the GPRC5D locus were also identified by scCNVseq with monoallelic and biallelic deletions in 11.9% and 2.7% of the cells, respectively. Clonal biallelic loss of GPRC5D post GPRC5DxCD3 TCE was detected in one patient who harbored a monoallelic loss in 79.2% of the cells pre-TCE. With regard to point mutations, in one patient progressing from a durable CR on BCMA TCE, we observed an acquired mono-allelic loss of TNFRSF17 (scCNV) coupled with de novo mutation in TNFRSF17 extracellular domain c.81G>C [p.(R27P)]. This point R27P mutation is predicted to be damaging to BCMA (Polyphen) with disruption of several H-bonds between R27 and C24, Q25, S29, S30 and T32 of BCMA extracellular aa residues. Importantly, molecular dynamic simulations of WT vs. mutant R27P using publicly deposited crystal structural of BCMA bound to anti-BCMA Ab (J22.9-xi) (PBD ID 4ZFO) demonstrated that this mutation disrupts all H-bonds between BCMA and the light chain of chimeric mouse/human anti-BCMA Ab (J22.9-xi). Functionally, primary CD138+ cells with mutant BCMA [p.(R27P)] as well as K562 cells transduced with mutant BCMA [p.(R27P)] were completely resistant to BCMAxCD3 cytotoxicity with teclistamab and elranatamab compared to cells with WT BCMA. While structural alterations of TNFRSF17 and GPRC5D remain relatively rare, we have identified biallelic loss of TNFRSF17 post BCMA CAR T and BCMAxCD3 TCE therapy and herein reported the first case of biallelic loss of GPRC5D post GPRC5DxCD3 TCE treatment. Importantly, we also identified a monoallelic loss of TNFRSF17 (del16p) coupled with BCMA extracellular domain point mutation [p.(R27P)] that confers resistance to two BCMAxCD3 TCEs in MM. Therefore, in addition to structural alterations (biallelic loss of TNFRSF17 or GPRC5D), antigen escape resulting from non-truncating missense point mutations in BCMA extracellular domain also mediate resistance to targeted-immunotherapies.

Multisite Qualification of an Automated Incubator and Colony Counter for Environmental and Bioburden Applications in Pharmaceutical Microbiology.

Traditional microbiological techniques have been used for well over a century as the basis for contamination testing of pharmaceutical products and processes. With more recent focus on faster product release and concerns around the integrity of the test data, new technologies have been implemented to detect and enumerate organisms faster and provide paperless processes to minimize data integrity issues. Manual colony counting technologies, where incubation is performed in a standard incubator, and the plate is manually transferred to the colony counter for a single read at the end of incubation, have been used for many years to reduce the potential for human error; however, they pose validation challenges due to poor counting accuracy. Colony counters that automatically perform both the incubation and enumeration functions (multiple enumeration calculations through the incubation phase) have recently been implemented for quality control (QC) laboratory analytical processes, supporting a cGMP environment. This article summarizes the findings of eight companies demonstrating the qualification of an automated colony counter technology to perform the majority of microbial tests required for QC, environmental monitoring, and bioburden for in-process, bulk drug substance, and water system testing. Comparable analytical performance and time to result data generated during individual studies at all companies allows the system to be qualified and implemented for cGMP processes while reducing data integrity risks.

The Assembled Genome of the Stroke-Prone Spontaneously Hypertensive Rat.

We report the creation and evaluation of a de novo assembly of the genome of the spontaneously hypertensive rat, the most widely used model of human cardiovascular disease. The genome is assembled from long read sequencing (PacBio HiFi and continuous long read data [CLR]) and scaffolded with long-range structural information obtained from Bionano optical maps and proximity ligation sequencing proximity analysis of the genome. The genome assembly was polished with Illumina short reads. Completeness of the assembly was investigated using Benchmarking Universal Single Copy Orthologs analysis. The genome assembly was also evaluated with the rat reference gene set, using NCBI automated protocols. We also generated orthogonal single molecule transcript sequence reads (Iso-Seq) from 8 tissues and used them to validate the coding assembly, to annotate the assembly with RNA transcripts representing unique full length transcript isoforms for each gene and to determine whether divergences between RefSeq sequences and the assembly were attributable to assembly errors or polymorphisms. The assembly analysis indicates that this assembly is comparable in contiguity and completeness to the current rat reference assembly, while the use of HiFi sequencing yields an assembly that is more correct at the single base level. Synteny analysis was performed to uncover the extent of synteny and the presence and distribution of chromosomal rearrangements between the reference and this assembly. The resulting genome assembly is reference quality and captures significant structural variation.

Methyl-SNP-seq reveals dual readouts of methylome and variome at molecule resolution while enabling target enrichment.

Covalent modifications of genomic DNA are crucial for most organisms to survive. Amplicon-based high-throughput sequencing technologies erase all DNA modifications to retain only sequence information for the four canonical nucleobases, necessitating specialized technologies for ascertaining epigenetic information. To also capture base modification information, we developed Methyl-SNP-seq, a technology that takes advantage of the complementarity of the double helix to extract the methylation and original sequence information from a single DNA molecule. More specifically, Methyl-SNP-seq uses bisulfite conversion of one of the strands to identify cytosine methylation while retaining the original four-bases sequence information on the other strand. As both strands are locked together to link the dual readouts on a single paired-end read, Methyl-SNP-seq allows detecting the methylation status of any DNA even without a reference genome. Because one of the strands retains the original four nucleotide composition, Methyl-SNP-seq can also be used in conjunction with standard sequence-specific probes for targeted enrichment and amplification. We show the usefulness of this technology in a broad spectrum of applications ranging from allele-specific methylation analysis in humans to identification of methyltransferase specificity in complex bacterial communities.

Differential Expression Analysis of Nothobranchius furzeri Transposable Elements from RNA-seq Data.

Transposable elements (TEs) comprise large fractions of eukaryotic genomes, but their repetitive nature and high copy number makes bioinformatic analyses more complex. Here, we report three robust pipelines to analyze TE expression from RNA-seq data in a non-model organism, the African turquoise killifish Nothobranchius furzeri Our protocol can be run with either a genomic or transcriptomic reference depending on available computational resources, with options both for limited memory usage and for more computationally intensive analyses. Our protocol leverages both standard software for classical RNA-seq analysis pipelines as well as software specialized for TEs. This protocol uses input RNA-seq data from Illumina reads and can use data in either single-end or paired-end layout. Here, we show how to start from input RNA-seq data from aging killifish tissues using a publicly available data set from which we take single and paired reads, trim adapters, align and count trimmed reads, and perform differential expression analyses for TEs.

A high-quality genome assembly of Lactarius hatsudake strain JH5.

Lactarius hatsudake is a species of Lactarius commonly found in pine forests, is edible with a delicious and nutritious fruiting body, and exhibits medicinal properties. It is an ideal natural multifunctional food with bioactive components including fungal polysaccharides, crude fiber, unsaturated fatty acids, nucleic acid derivatives, various amino acids, and vitamins. However, biological and genomic analyses of this mycorrhizal mushroom are sparse, thereby hindering large-scale cultivation. Previously, we isolated and screened L. hatsudake JH5 strains and have applied our garnered knowledge to the large-scale cultivation of mycorrhizal seedlings. In this study, we produced a high-quality genome assembly of L. hatsudake JH5 by combining Illumina paired-end and PacBio single molecule real-time sequencing, resulting in PacBio single molecule real-time reads of 7.67 Gb and Illumina Pair-End reads of 1,560 Mb. Based on the distribution of k-mer frequencies, the genome size of this strain was estimated to be 63.84 Mb (1.14% heterozygosity). Based on de novo genome assembly, the final genome size was determined to be 76.7 Mb, with scaffold N50 of 223.2 kb and N90 of 54.5 kb, and a GC content of 54.38%. BUSCO assessment showed that genome completeness was 89.0%. The N50 length of the JH5 genome was 43.6% longer than that of the previously published L. hatsudake MG20 genome. This high-quality L. hatsudake genome assembly will facilitate research on the functional genome, molecular breeding, yield enhancement, and sustainability of L. hatsudake cultivation.

Local bit-line shared pass-gate 8T SRAM based energy efficient and reliable In-Memory Computing architecture

The In-Memory Computing (IMC) architecture based on Conventional 6T, 8T, and 10T SRAM suffers from compute disturbance, compute-failure, and half-select issues, which affect the reliability of In-Memory Boolean Computation (IMBC) operations. To overcome these problems, local bit-line Shared pass-gate Dual-Port 8T (SDP8T) SRAM-based IMC architecture is proposed to perform energy-efficient IMBC operations. The local bit-line shared pass-gate structure addresses the half select issues with a small area overhead and achieves higher array efficiency by incorporating the bit-interleave architecture. The virtual-VSS write-assist is used in SDP8T SRAM to improve the write-margin yield (μ−3σ) by 48.99%, and multi-VTH technique improves Decoupled Read-Margin (DRM) yield by 5.26% when compared to DP8T SRAM. The Dynamical Reset Word Line (DRWL) scheme is proposed to resolve the sneak current problem and make the proposed IMC architecture more resilient to compute disturbance at non-read decouple paths during IMBC operations. Further, the Reference-based Reconfigurable Sense Amplifier (RRCSA) scheme is proposed to achieve reliable (compute-failure free) sensing for IMBC on four operands simultaneously in a single cycle, normal read, and Binary Content Addressable Memory (BCAM) operations. The 4 Kb SRAM array is implemented in 65-nm CMOS technology to analyze the SDP8T-IMC architecture. The operating frequency of 1190 MHz and average-energy consumption of 18.56 fJ/bit are achieved during IMBC operation at 1V. For BCAM operations, it achieves 0.60 fJ/search/bit energy consumption in the worst case (i.e., all data mismatch) at 1V. Cumulatively, the proposed SDP8T-IMC architecture has the highest figure of merits than the recently reported IMC architecture.

Capturing Structural Variants of Herpes Simplex Virus Genome in Full Length by Oxford Nanopore Sequencing.

ABSTRACTGenome sequencing and assembly of viral genomes within the Herpesviridae family, particularly herpes simplex virus (HSV), have been challenging due to the large size (~154 Kb), high GC content (68%), and nucleotide variations arising during replication. Oxford Nanopore Technology (ONT) has been successful in obtaining read lengths ranging from 100 Kb up to 2.3 Mb. We have optimized DNA extraction and sequencing with ONT to capture the whole genome of HSV-1 as a single read. Although previous studies described the presence of four different genome isomers of HSV, we provided the first report on capturing all four variants’ full-length genome as single reads. These isomers were found to be present in almost equal proportion in the sequenced DNA preparation.IMPORTANCE With the advent of next-generation sequencing platforms, genome sequencing of viruses can be performed in a relatively shorter time frame in even the most austere conditions. Ultralong read sequencing platforms, such as Oxford Nanopore Technology (ONT), have made it possible to capture the full-length genome of DNA viruses as a single read. By optimizing ONT for this purpose, we captured the genome (~154 Kb) of a clinical strain of herpes simplex virus 1 (HSV-1). Additionally, we captured full-length sequences of the four isomers of lab-grown HSV-1 virus and were able to determine the frequency of each within the isogenic population. This method will open new directions in studying the significance of these isomers and their clinical relevance to HSV-1 infections. It will also improve basic studies on the recombination and replication of this virus.

How do emerging long-read sequencing technologies function in transforming the plant pathology research landscape?

Long-read sequencing technologies are revolutionizing the sequencing and analysis of plant and pathogen genomes and transcriptomes, as well as contributing to emerging areas of interest in plant-pathogen interactions, disease management techniques, and the introduction of new plant varieties or cultivars. Long-read sequencing (LRS) technologies are progressively being implemented to study plants and pathogens of agricultural importance, which have substantial economic effects. The variability and complexity of the genome and transcriptome affect plant growth, development and pathogen responses. Overcoming the limitations of second-generation sequencing, LRS technology has significantly increased the length of a single contiguous read from a few hundred to millions of base pairs. Because of the longer read lengths, new analysis methods and tools have been developed for plant and pathogen genomics and transcriptomics. LRS technologies enable faster, more efficient, and high-throughput ultralong reads, allowing direct sequencing of genomes that would be impossible or difficult to investigate using short-read sequencing approaches. These benefits include genome assembly in repetitive areas, creating more comprehensive and exact genome determinations, assembling full-length transcripts, and detecting DNA and RNA alterations. Furthermore, these technologies allow for the identification of transcriptome diversity, significant structural variation analysis, and direct epigenetic mark detection in plant and pathogen genomic regions. LRS in plant pathology is found efficient for identifying and characterization of effectors in plants as well as known and unknown plant pathogens. In this review, we investigate how these technologies are transforming the landscape of determination and characterization of plant and pathogen genomes and transcriptomes efficiently and accurately. Moreover, we highlight potential areas of interest offered by LRS technologies for future study into plant-pathogen interactions, disease control strategies, and the development of new plant varieties or cultivars.

Poster 197: Understanding the Biological Pathway of Progression of Hip OA Disease through Transcriptome Analysis

Poster 197: Understanding the Biological Pathway of Progression of Hip OA Disease through Transcriptome Analysis