Sequencing Platforms Research Articles

When multiple primary lung cancers express the same rare mutation: a case report

The debate continues whether the expression of the same rare genetic mutation in multiple primary lung cancers suggests intrapulmonary metastasis or truly multiple primary lung cancers. We report a case of a 54-year-old female patient who presented with multiple nodules in the right lung discovered during a routine examination, persisting for six months. The patient had three central lesions in the right lung’s upper, middle, and lower lobes. She underwent thoracoscopic wedge resection, and the postoperative pathology reported two minimally invasive adenocarcinoma and one adenocarcinoma in situ. Interestingly, genetic testing for lung cancer-related driver genes revealed the presence of the rare RET mutation in all three nodules. This led us to speculate that these nodules might have the exact origin rather than being multiple primaries. To verify this hypothesis, we conducted further testing on these nodules, including whole-exome sequencing (The NGS data was generated from the Illumina sequencing platform by Novogene Co. Ltd, Beijing, China). The results indicated that although all three nodules expressed the RET mutation, there was significant heterogeneity in the gene mutations (differences in the number of cellular mutations, substitution composition levels, and clustering analysis of the three nodules). Thus, the patient was considered to have multiple primary lung cancers. In such cases, whole-exome sequencing can distinguish whether the nodules have the exact origin.

Abstract A009: Integrative multiomic analysis of extracellular vesicle transcriptomics profiling combined with cfDNA methylation reveals improved stratification of low-risk and high- risk prostate cancer patients in urine-based liquid biopsy

Abstract Introduction: Prostate cancer (PCa) ranks as the second most frequently diagnosed cancer and the sixth most prevalent cause of cancer-related mortality in men globally. In this study, we employ a multiomic approach that utilizes both urine cfDNA and extracellular vesicle (EV) RNA-derived analytes to improve the risk stratification of individuals with prostate cancer and compare this to multi-parametric MRI performance as well as risk calculators in the same cohort. Materials and Methods: Urine was collected from 95 individuals comprising 51 benign or low-risk (Grade Group (GG) <=1), 10 intermediate-risk (GG2) and 44 high-risk PCa patients (GG 3-5). EV-RNA and cfDNA were concurrently isolated from each urine specimen to exploit complementary information. We developed an EV-RNA sequencing platform targeting mRNAs and lncRNAs and targeted 50 million reads per sample; and cfDNA methylome profiling reached an equivalent sequencing depth. Expression of EV-RNA and splice variant Differential Transcript Usage (DTU) and cfDNA methylation patterns were analyzed using Bio-Techne’s multiomic platform. Machine learning-based feature selection algorithms identified biomarker signatures from each analyte. Receiver-operator characteristic curves (ROC) were generated utilizing leave-one-out cross-validation of naïve Bayes classifier models to compute the area under the curve (AUC). Individual signatures were integrated to create a multiomic classifier. Results: Differential gene expression (DEx) analysis identified 18 DEx genes between low and high-risk patients with both known and novel implications in PCa. Splice variant analysis unveiled 60 genes previously implicated in PCa with DTU. Over 18,000 differentially methylated bases were detected between high and low-risk PCa patients. Feature selection analysis identified the top ten features of EV-RNA expression, splice variants, and cfDNA methylation, resulting in an integrative multi-analyte signature. The multiomic signature demonstrated an AUC of 0.92, surpassing any individual analyte’s performance, as well as the performance achieved by PSA (AUC = 0.52) and MRI PI RADS(AUC=0.65). Conclusions: While biomarker signatures obtained from each analyte in this study resulted in effective stratification of PCa risk, the multiomic signature further improved the discriminatory power—underscoring the complementary nature of the signals. Thus, a multiomic biomarker discovery strategy leveraging cfDNA and EV cargo exhibits significant potential as a risk assessment tool for high-grade prostate cancer. This approach can facilitate more informed decision-making in the context of biopsy procedures. Citation Format: Sudipto K Chakrabortty, Dulaney Miller, Kyle Manning, Rikky Xing, Jeff Cole, Christopher Benway, Sinead Nguyen, Allan George, Yiyuan Yao, Elena M Cortizas, Christian Ray, Siva Gowrisankar, Seth Yu, Allan Pollack, Sandra M Gaston, Sanoj Punnen, Johan Skog. Integrative multiomic analysis of extracellular vesicle transcriptomics profiling combined with cfDNA methylation reveals improved stratification of low-risk and high- risk prostate cancer patients in urine-based liquid biopsy [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr A009.

Improved resolution of microbial diversity in deep-sea surface sediments using PacBio long-read 16S rRNA gene sequencing

ABSTRACT 16S rRNA gene sequencing is the gold standard for identifying microbial diversity in environmental communities. The Illumina short-read platform is widely used in marine environment studies due to its cost-effectiveness and high accuracy, but its limited read length restricts taxonomic identification mainly to genus or family levels. Recently, the PacBio long-read sequencing platform was developed. This method has exceptional base-level resolution exceeding 99%, thereby effectively mitigating the challenges associated with high error rates commonly observed in long-read sequencing technologies. However, few studies have compared the PacBio long-read and Illumina short-read platforms in marine deep-sea sediments. Here, the PacBio long-read and Illumina short-read platforms were compared with samples collected from the deep-sea surface sediments from the cold seep in the Shenhu area of the South China Sea offshore Pearl River Estuary. Comparisons revealed a more comprehensive taxonomic identification, α-diversity, and β-diversity by PacBio long-reads. The PacBio long-read platform exhibited higher classified rates and classified taxonomy at all levels, particularly at the species level. The PacBio long-read platform was also more accurate at capturing fine spatial-scale variations in microbial communities in sediments. Our studies will facilitate the selection of 16S rRNA sequencing platforms for investigating fine spatial-scale patterns in microbial communities in deep-sea surface sediments and serve as a crucial methodological reference for future studies on microbial diversity. IMPORTANCE The PacBio long-read platform, with its exceptional base-level resolution exceeding 99%, has advanced our comprehension of deep-sea microbial diversity. By comparing microbial community analyses conducted using the Illumina short-read and PacBio long-read sequencing platforms, we have provided an enhanced understanding of fine spatial-scale patterns in microbial community diversity with depth across a deep-sea sediment core, as well as methodological insights that will be valuable for future research in this field.

Abstract 4135951: Single Nuclei RNA Sequencing Reveals Distinct Cellular Composition of Pericoronary Adipose Tissue

Introduction: Adipose tissue is a metabolically active organ with local paracrine interactions on adjacent tissues. Pericoronary adipose tissue (PcAT) is an emerging cardiovascular disease (CVD) risk factor and likely has paracrine effects on coronary vasculature that may promote coronary artery disease (CAD) development. PcAT may be functionally and clinically distinct from epicardial adipose tissue (EAT) given its proximity to the coronary artery adventitia. The cellular composition of PcAT and EAT and whether they have unique inflammatory cell signatures and functional expression at a single cell level has not been explored. Hypothesis: PcAT will have diverse cellular composition with heightened inflammatory cell content compared to EAT. Methods: Visual dissection of paired EAT not adjacent to an epicardial coronary artery and PcAT in direct apposition to an epicardial artery (left anterior descending artery) was performed from a single human heart immediately after explant (prior to heart transplantation). Nuclei were isolated using the Chromium Nuclei Isolation Kit (10x Genomics) with RNAse inhibitor. Cells were counted with a Cellometer K2 and Chromium Next GEM Single Cell libraries were prepared, followed by reverse transcription, PCR and NovaSeq 6000 platform sequencing. Raw sequence reads from single nuclei RNA-seq (snRNA-seq) were processed and after QC filtering, cells were clustered using Seurat. Clusters were annotated using singleR. Results: In PcAT and EAT, >7000 cells were successfully extracted with 73755 and 48750 mean snRNA-seq reads per cell, respectively. snRNA-seq cellular composition analysis delineated a heightened inflammatory milieu and distinct cellular composition of human PcAT vs. EAT. A UMAP (Uniform Manifold Approximation and Projection) plot displays higher inflammatory cell infiltrate with a neutrophil predominance and lesser adipocyte composition in PcAT compared with EAT ( Figure 1) . Conclusions: We have generated snRNA-seq data from human PcAT and shown distinct cellular composition compared to EAT. Given the proximity of PcAT to coronary vasculature, these results are supportive of paracrine inflammatory effects and highlight adipose tissue biology in cardiovascular disease. Understanding this biology may identify novel therapeutic targets for CVD.

Matching excellence: Oxford Nanopore Technologies’ rise to parity with Pacific Biosciences in genome reconstruction of non-model bacterium with high G+C content

The reconstruction of complete bacterial genomes is essential for microbial research, offering insights into genetic content, ontology and regulation. While Pacific Biosciences (PacBio) provides high-quality genomes, its cost remains a limitation. Oxford Nanopore Technologies (ONT) offers long reads at a lower cost, yet its error rate raises scepticism. Recent ONT advancements, such as new Flow cells (R10.4.1), chemistry (V14) and duplex mode, improve data quality. Our study compares ONT with PacBio and Illumina, including hybrid data. We used Propionibacterium freudenreichii, a bacterium with a genome known for being difficult to reconstruct. By combining data from ONT’s Native Barcoding and a custom-developed BARSEQ method, we achieved high-quality, near-perfect genome assemblies. Our findings demonstrate, for the first time, that the combination of nanopore-only long-native with shorter PCR DNA reads (~3 kb) results in high-quality genome reconstruction, comparable to hybrid data assembly from two sequencing platforms. This endorses ONT as a cost-effective, stand-alone strategy for bacterial genome reconstruction. Additionally, we compared methylated motif detection between PacBio and ONT R10.4.1 data, showing that results comparable to PacBio are achievable using ONT, especially when utilizing the advanced Nanomotif tool.

EPCO-18. DECIPHERING SPATIAL DIVERSITY OF GLIOBLASTOMA GENETIC ARCHITECTURE

Abstract Glioblastoma (GBM) is hallmarked by profound inter- and intratumoral heterogeneity. Current research has mapped key genetic drivers to distinct transcriptional profiles within GBM. Nevertheless, the intricate interactions between genetic alterations and spatial-transcriptional heterogeneity remain elusive. We utilized nestin-Tva C57BL/6 mice to induce de novo GBM via oncogene overexpression alongside shRNA-mediated silencing or deletion of tumor suppressors. We modeled critical driver mutations: PDGFB, NF1, and EGFR. Employing 10X Genomics platform for single-cell RNA sequencing, combined with spatially resolved transcriptomics and proteomics (Nanostring GeoMx), we integrated data using both horizontal (mutual nearest neighbors) and vertical (weighted nearest neighbors) approaches, analyzed through the SPATA2 software. Advanced computational techniques, including graph neural networks and single-cell deconvolution, were leveraged to unravel the genotypic and spatial variability within tumors and their microenvironments. Our findings uncover persistent cellular heterogeneity across diverse genetic contexts. However, specific genetic mutations precipitated distinct dominant transcriptional states: NF1 and EGFR mutations drove mesenchymal and astrocytic-like states, respectively, whereas PDGFB fostered a neural progenitor/cell-like state. These transcriptional shifts were closely linked to unique microenvironmental modifications, such as elevated neuronal signaling in PDGFB-driven GBMs and significant immune infiltration in NF1 and EGFR models. Through weighted co-expression network analysis (WGCNA) and gene set enrichment analysis (GSEA) paired with spatial-niche deconvolution, we identified a mesenchymal transition leading to an immunosuppressive microenvironment in NF1-loss driven GBMs and increased lymphocyte presence around blood vessels in EGFR-amplified GBMs. These patterns were consistent with human spatially resolved transcriptomic data, emphasizing the genetic complexity and heterogeneity of human GBMs. Our genetically engineered mouse models serve as a robust platform for dissecting GBM with defined genetic mutations. Leveraging sophisticated analytical techniques and computational modeling, this study underscores the profound interplay between genetic drivers and the tumor microenvironment, paving the way for targeted therapeutic strategies and precision medicine in GBM.

QLTI-06. NEXT GENERATION SEQUENCING SIGNIFICANTLY IMPROVES THE DIAGNOSTIC ACCURACY IN GLIOBLASTOMAS

Abstract The 2021 WHO Classification of CNS Tumours recognizes the presence of TERT promoter (pTERT) mutations, combined +7/-10 chromosome copy-number alterations, or EGFR amplification as a defining molecular feature(s) of glioblastoma, independent of histology. We evaluated these biomarkers in a cohort of Indian patients using a single-run next-generation sequencing (NGS) platform at a relatively low depth of 100. Seventy-four adult diffuse gliomas were selected from the Exsegen Genomics Research Pvt Ltd Biobank established during the trial CTRI/2021/09/036861 after reviewing their clinical and pathological data. Paired surgical tissue and blood samples underwent whole-exome sequencing on an Illumina NovaSeq-6000 (Illumina, San Diego, USA). Single-nucleotide variations (SNVs) were processed using the DRAGEN pipeline to generate Mutation Annotation Format (MAF) files. Copy number variations (CNVs) analysis was performed using GATK and GISTIC2.0. Thirty-nine glioma samples with IDH1R132H mutations were excluded. A total of 32/35 (91.4%) IDH-wildtype tumours met the 2021 WHO criteria for glioblastoma, IDH-wildtype and were included. Twenty-four glioblastomas also underwent whole-transcriptome analysis. Microvascular proliferation (n=24, 75%) and necrosis (n=30, 93.9%) were present in the majority. pTERT mutations were identified in 23 (71.9%) samples, with C228T mutations (n=15/23, 65.2%) being more common than C250T mutations (n=8/23, 34.8%). EGFR amplification, defined as ≥5 copies by NGS CNV, was seen in 15 (46.9%) samples, with a strong correlation between EGFR CNV and logEGFR expression (r=0.79; p=0.017). Whole-arm +7/-10 genotype was evident in 17 (53.1%) tumours, and another 5 (15.6%) showed partial copy-number alterations. Notably, two gliomas without necrosis and proliferation initially diagnosed as oligodendrogliomas due to misinterpretation of the IDH immunostain, were reclassified as glioblastoma, IDH-wildtype. The data was validated using Sanger Sequencing and targeted panel sequencing to a depth of 500. Even low depth NGS sequencing, that is cost effective and time efficient offers significant improvements in diagnostic molecular neuropathology.

Parental Reconstruction from a Half-Sib Population of Stoneless Jujube Ziziphus jujuba Mill. Based on Individual Specific SNP Markers Using Multiplex PCR

The selection of unique and individual-specific SNPs is important as compared with universal SNPs for individual identification. Therefore, the main significance of this research is the selection of specific SNPs in male parent and the identification of offspring with these specific SNPs in their genome by multiplex PCR, which is utilized for genotyping of 332 half-sib plants of Ziziphus jujuba.This cost-effective method makes as much as possible to utilize the same amount of each pair of various targeted loci primers. After PCR amplification of targeted genome parts, the mixed products can be directly used in a next-generation sequencing platform. We concomitantly amplified 10 unique SNP loci at 10 different chromosomes of male JingZao 39 plants in 332 half-sib plants and sequenced them on the Illumina Novaseq 6000 platform. Analysis of SNP genotyping accuracy of 332 half-sib plants showed that all 10 unique SNPs in all 332 plants were correctly amplified in this multiplex PCR method. Furthermore, based on Mendelian inheritance, we identified 124 full-sib plants that have 10 unique SNPs in their genomes. These results were further confirmed by whole genome resequencing of 82 randomly selected half-sib plants, and the identity-by-descent values of all full-sib plants were between 0.4399 to 0.5652. This study displayed a cost-effective multiplex PCR method and proper identification of pollen parent through specific SNPs in half-sib progenies and firstly obtained a full-sib population between ‘Wuhezao’ and ‘JingZao 39’, segregating for stone and stoneless fruit.

PATH-47. AGE-, SEX-, AND GRADE-ASSOCIATED MOLECULAR DIFFERENCES IN A MULTI-INSTITUTIONAL COHORT OF CHOROID PLEXUS TUMORS

Abstract BACKGROUND Choroid plexus tumors (CPT) are central nervous system tumors where prognosis has been correlated to histologic grade, with aggressive clinical behavior and reduced survival rate in higher grade cases. Here, we present a genomic survey of a large multi-institutional cohort of CPTs across all grades. MATERIAL AND METHODS Fifty-eight CPT samples were analyzed by comprehensive genomic profiling (CGP) by a hybrid capture-based DNA sequencing platform (FoundationOne®CDx). Pathology reports, histopathology reviews, and patient clinical data were assessed. RESULTS Our cohort included 11 choroid plexus papillomas (CPP; grade 1), 16 atypical CPP (grade 2), and 31 choroid plexus carcinomas (CPC; grade 3). Males were slightly more affected than females (31 vs. 27 cases). Median patient age at tissue sampling was 11 years (range: 1–72 years). Median age of patients with CPC was younger at 3 years compared CPP at 34 years (p < 0.01). Genomic analyses identified three frequent, mutually exclusive mutations in TP53, TERTp, and DAXX. TP53 mutations (n = 15, 26%) were significantly more prevalent in CPC (n=14 CPC, p=0.0003), and were identified predominantly in children (n=12 CPC at <20 years). By contrast, TERT promoter mutations (TERTp; n = 5, 8.6%) were identified exclusively in CPP (p=0.019), predominantly grade 2 (4 of 5 cases), and exclusively in adult patients, with a median age of 48 years. DAXX mutations (n=4, 6.9%) were more common in CPC (n=3). Other alterations included PTEN (n=4, all adults) and MYCN amplification (n=3, all children <6 years), both exclusively in CPC. In 21 cases, including 9 out of the 11 Grade 1 CPP, no known cancer mutation was detected. CONCLUSION This study provides comprehensive genomic profiling of CPTs, highlighting distinct genetic alterations associated with different histological grades and patient demographics. These findings may inform future research and therapeutic strategies targeting specific molecular pathways in CPTs.

MobiChIP: a compatible library construction method of single-cell ChIP-seq based droplets.

To illustrate epigenetic heterogeneity, versatile tools of single-cell ChIP-seq (scChIP-seq) are essential for both convenience and accuracy. We developed MobiChIP, a compatible ChIP-seq library construction method based on current sequencing platforms for single-cell applications. MobiChIP efficiently captures fragments from tagmented nuclei across various species and allows sample mixing from different tissues or species. This strategy offers robust nucleosome amplification and flexible sequencing without customized primers. MobiChIP reveals regulatory landscapes of chromatin with active (H3K27ac) and repressive (H3K27me3) histone modification in peripheral blood mononuclear cells (PBMCs) and accurately identifies epigenetic repression of the Hox gene cluster, outperforming ATAC-seq. Meanwhile, we also integrated scChIP-seq with scRNA-seq to further illustrate cellular genetic and epigenetic heterogeneity.

Leveraging large-scale Mycobacterium tuberculosis whole genome sequence data to characterise drug-resistant mutations using machine learning and statistical approaches

Tuberculosis disease (TB), caused by Mycobacterium tuberculosis (Mtb), is a major global public health problem, resulting in > 1 million deaths each year. Drug resistance (DR), including the multi-drug form (MDR-TB), is challenging control of the disease. Whilst many DR mutations in the Mtb genome are known, analysis of large datasets generated using whole genome sequencing (WGS) platforms can reveal new variants through the assessment of genotype-phenotype associations. Here, we apply tree-based ensemble methods to a dataset comprised of 35,777 Mtb WGS and phenotypic drug-susceptibility test data across first- and second-line drugs. We compare model performance across models trained using mutations in drug-specific regions and genome-wide variants, and find high predictive ability for both first-line (area under ROC curve (AUC); range 88.3–96.5) and second-line (AUC range 84.1–95.4) drugs. To aggregate information from low-frequency variants, we pool mutations by functional impact and observe large improvements in predictive accuracy (e.g., sensitivity: pyrazinamide + 25%; ethionamide + 10%). We further characterise loss-of-function mutations observed in resistant phenotypes, uncovering putative markers of resistance (e.g., ndh 293dupG, Rv3861 78delC). Finally, we profile the distribution of known DR-associated single nucleotide polymorphisms across discretised minimum inhibitory concentration (MIC) data generated from phenotypic testing (n = 12,066), and identify mutations associated with highly resistant phenotypes (e.g., inhA − 779G > T and 62T > C). Overall, our work demonstrates that applying machine learning to large-scale WGS data is useful for providing insights into predicting Mtb binary drug resistance and MIC phenotypes, thereby potentially assisting diagnosis and treatment decision-making for infection control.

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.

Cross-comparison of gut metagenomic profiling strategies

The rapid advancements in sequencing technologies and bioinformatics have enabled metagenomic research of complex microbial systems, but reliable results depend on consistent laboratory and bioinformatics approaches. Current efforts to identify best practices often focus on optimizing specific steps, making it challenging to understand the influence of each stage on microbial population analysis and compare data across studies. This study evaluated DNA extraction, library construction methodologies, sequencing platforms, and computational approaches using a dog stool sample, two synthetic microbial community mixtures, and various sequencing data sources. Our work, the most comprehensive evaluation of metagenomic methods to date. We developed a software tool, termed minitax, which provides consistent results across the range of platforms and methodologies. Our findings showed that the Zymo Research Quick-DNA HMW MagBead Kit, Illumina DNA Prep library preparation method, and the minitax bioinformatics tool were the most effective for high-quality microbial diversity analysis. However, the effectiveness of pipelines or method combinations is sample-specific, making it difficult to identify a universally optimal approach. Therefore, employing multiple approaches is crucial for obtaining reliable outcomes in microbial systems.

Illumina SBS Sequencing and DNBSEQ Perform Similarly for Single-Cell Transcriptomics

Background/Objectives: High-throughput single-cell RNA sequencing (scRNA-seq) workflows produce libraries that demand extensive sequencing. However, standard next-generation sequencing (NGS) methods remain expensive, contributing to the high running costs of single-cell experiments and often negatively affecting the sample numbers and statistical strength of such projects. In recent years, a plethora of new sequencing technologies have become available to researchers through several manufacturers, often providing lower-cost alternatives to standard NGS. Methods: In this study, we compared data generated from mouse scRNA-seq libraries sequenced with both standard Illumina sequencing by synthesis (Illumina SBS) and MGI’s DNA nanoball sequencing (DNBSEQ). Results: Our findings reveal similar overall performance using both technologies. DNBSEQ exhibited mildly superior sequence quality compared to Illumina SBS, as evidenced by higher Phred scores, lower read duplication rates and a greater number of genes mapping to the reference genome. Yet these improvements did not translate into meaningful differences in single-cell analysis parameters in our experiments, including detection of additional genes within cells, gene expression saturation levels and numbers of identified cells, with both technologies demonstrating equally robust performance in these aspects. The data produced by both sequencing platforms also produced comparable analytical outcomes for single-cell analysis. No significant difference in the annotation of cells into different cell types was observed and the same top genes were differentially expressed between populations and experimental conditions. Conclusions: Overall, our data demonstrate that alternative technologies can be applied to sequence scRNA-seq libraries, generating virtually indistinguishable results compared to standard methods, and providing cost-effective alternatives.

Setting Up an NGS Sequencing Platform and Monitoring Molecular Markers of Anti-Malarial Drug Resistance in Djibouti

Djibouti is confronted with malaria resurgence, with malaria having been occurring in epidemic proportions since a decade ago. The current epidemiology of drug-resistant Plasmodium falciparum is not well known. Molecular markers were analyzed by targeted sequencing in 79 P. falciparum clinical isolates collected in Djibouti city in 2023 using the Miseq Illumina platform newly installed in the country. The objective of the study was to analyze the key codons in these molecular markers associated with antimalarial drug resistance. The prevalence of the mutant Pfcrt CVIET haplotype (92%) associated with chloroquine resistance and mutant Pfdhps-Pfdhfr haplotypes (7.4% SGEA and 53.5% IRN, respectively) associated with sulfadoxine-pyrimethamine resistance was high. By contrast, Pfmdr1 haplotypes associated with amodiaquine (YYY) or lumefantrine (NFD) resistance were not observed in any of the isolates. Although the “Asian-type” PfK13 mutations associated with artemisinin resistance were not observed, the “African-type” PfK13 substitution, R622I, was found in a single isolate (1.4%) for the first time in Djibouti. Our genotyping data suggest that most Djiboutian P. falciparum isolates are resistant to chloroquine and sulfadoxine-pyrimethamine but are sensitive to amodiaquine, lumefantrine, and artemisinin. Nonetheless, the presence of an isolate with the R622I PfK13 substitution is a warning signal that calls for a regular surveillance of molecular markers of antimalarial drug resistance.

Gapless assembly of complete human and plant chromosomes using only nanopore sequencing.

The combination of ultra-long (UL) Oxford Nanopore Technologies (ONT) sequencing reads with long, accurate Pacific Bioscience (PacBio) High Fidelity (HiFi) reads has enabled the completion of a human genome and spurred similar efforts to complete the genomes of many other species. However, this approach for complete, "telomere-to-telomere" genome assembly relies on multiple sequencing platforms, limiting its accessibility. ONT "Duplex" sequencing reads, where both strands of the DNA are read to improve quality, promise high per-base accuracy. To evaluate this new data type, we generated ONT Duplex data for three widely studied genomes: human HG002, Solanum lycopersicum Heinz 1706 (tomato), and Zea mays B73 (maize). For the diploid, heterozygous HG002 genome, we also used "Pore-C" chromatin contact mapping to completely phase the haplotypes. We found the accuracy of Duplex data to be similar to HiFi sequencing, but with read lengths tens of kilobases longer, and the Pore-C data to be compatible with existing diploid assembly algorithms. This combination of read length and accuracy enables the construction of a high-quality initial assembly, which can then be further resolved using the UL reads, and finally phased into chromosome-scale haplotypes with Pore-C. The resulting assemblies have a base accuracy exceeding 99.999% (Q50) and near-perfect continuity, with most chromosomes assembled as single contigs. We conclude that ONT sequencing is a viable alternative to HiFi sequencing for de novo genome assembly, and provides a multirun single-instrument solution for the reconstruction of complete genomes.

Quantum sensing with optically accessible spin defects in van der Waals layered materials

Quantum sensing has emerged as a powerful technique to detect and measure physical and chemical parameters with exceptional precision. One of the methods is to use optically active spin defects within solid-state materials. These defects act as sensors and have made significant progress in recent years, particularly in the realm of two-dimensional (2D) spin defects. In this article, we focus on the latest trends in quantum sensing that use spin defects in van der Waals (vdW) materials. We discuss the benefits of combining optically addressable spin defects with 2D vdW materials while highlighting the challenges and opportunities to use these defects. To make quantum sensing practical and applicable, the article identifies some areas worth further exploration. These include identifying spin defects with properties suitable for quantum sensing, generating quantum defects on demand with control of their spatial localization, understanding the impact of layer thickness and interface on quantum sensing, and integrating spin defects with photonic structures for new functionalities and higher emission rates. The article explores the potential applications of quantum sensing in several fields, such as superconductivity, ferromagnetism, 2D nanoelectronics, and biology. For instance, combining nanoscale microfluidic technology with nanopore and quantum sensing may lead to a new platform for DNA sequencing. As materials technology continues to evolve, and with the advancement of defect engineering techniques, 2D spin defects are expected to play a vital role in quantum sensing.

Research on the Therapeutic Effect of Qizhu Anti Cancer Recipe on Colorectal Cancer Based on RNA Sequencing Analysis.

Colorectal cancer is one of the common malignant tumors in clinical practice, and traditional Chinese medicine, as an important adjuvant treatment method, plays important roles in the treatment of malignant tumors. This study aims to explore the mechanism of action of the Qizhu anti-cancer recipe on colorectal cancer through transcriptome sequencing. The control group and Qizhu anti-cancer recipe group were established separately, and sequencing of the cells of the two groups was performed using the Illumina sequencing platform. Two sets of Differentially Expressed Genes (DEGs) were screened using the DESeq2 algorithm, and Principal Component Analysis (PCA), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, Disease Ontology (DO), and Protein-Protein Interaction (PPI) were used to comprehensively analyze the molecular functions and signaling pathways enriched by DEGs. A total of 122 DEGs were identified through differential analysis, including 24 upregulated genes and 98 downregulated genes. GO analysis showed that DEGs were mainly enriched in functions such as alkaline phase activity, ion transport, cell differentiation, etc.; KEGG analysis showed that DEGs were mainly enriched in pathways such as Thiamine metabolism, apoptosis, signaling pathways regulating pluripotency of stem cells, cellular senescence and so on. Reactom analysis showed that DEGs were mainly enriched in response pathways such as EGR1,2,3 bind to the NAB2 promoter, EGR binds ARC gene, EGR-dependent NAB2 gene expression, etc.; DO analysis showed that differentially expressed genes were mainly enriched in diseases such as disease of cellular proliferation, disease of anatomical entity, organ system cancer, etc.; PPI analysis identified key differentially expressed genes, including DDIT3, CHAC1, TRIB3, and ASNS. Based on transcriptome sequencing and bioinformatics analysis, it was found that the Qizhu anti-cancer recipe may involve DEGs and signaling pathways in the treatment of colorectal cancer. Our study may provide potential drug targets for developing new treatment strategies for colorectal cancer.

The chromosome-level Elaeagnus mollis genome and transcriptomes provide insights into genome evolution, glycerolipid and vitamin E biosynthesis in seeds

Elaeagnus mollis, which has seeds with high lipid and vitamin E contents, is a valuable woody oil plant with potential for utilization. Currently, the biosynthesis and regulation mechanism of glycerolipids and vitamin E are still unknown in E. mollis. Here, we present the chromosome-level reference genome of E. mollis (scaffold N50: ~40.66Mbp, genome size: ~591.48Mbp) by integrating short-read, long-read, and Hi-C sequencing platforms. A total of 36,796 protein-coding sequences, mainly located on 14 proto-chromosomes, were predicted. Additionally, two whole genome duplication (WGD) events were suggested to have occurred ~54.07 and ~35.06 million years ago (MYA), with Elaeagnaceae plants probably experiencing both WGD events. Furthermore, the long terminal retrotransposons in E. mollis were active ~0.23MYA, and one of them was inferred to insert into coding sequence of the negative regulatory lipid synthesis gene, EMF2. Through transcriptomic and metabonomic analysis, key genes contributing to the high lipid and vitamin E levels of E. mollis seeds were identified, while miRNA regulation was also considered. This comprehensive work on the E. mollis genome not only provides a solid theoretical foundation and experimental basis for the efficient utilization of seed lipids and vitamin E, but also contributes to the exploration of new genetic resources.

Seq-Scope: repurposing Illumina sequencing flow cells for high-resolution spatial transcriptomics.

Spatial transcriptomics technologies aim to advance gene expression studies by profiling the entire transcriptome with intact spatial information from a single histological slide. However, the application of spatial transcriptomics is limited by low resolution, limited transcript coverage, complex procedures, poor scalability and high costs of initial setup and/or individual experiments. Seq-Scope repurposes the Illumina sequencing platform for high-resolution, high-content spatial transcriptome analysis, overcoming these limitations. It offers submicrometer resolution, high capture efficiency, rapid turnaround time and precise annotation of histopathology at a much lower cost than commercial alternatives. This protocol details the implementation of Seq-Scope with an Illumina NovaSeq 6000 sequencing flow cell, allowing the profiling of multiple tissue sections in an area of 7 mm × 7 mm or larger. We describe the preparation of a fresh-frozen tissue section for both histological imaging and sequencing library preparation and provide a streamlined computational pipeline with comprehensive instructions to integrate histological and transcriptomic data for high-resolution spatial analysis. This includes the use of conventional software tools for single-cell and spatial analysis, as well as our recently developed segmentation-free method for analyzing spatial data at submicrometer resolution. Aside from array production and sequencing, which can be done in batches, tissue processing, library preparation and running the computational pipeline can be completed within 3 days by researchers with experience in molecular biology, histology and basic Unix skills. Given its adaptability across various biological tissues, Seq-Scope establishes itself as an invaluable tool for researchers in molecular biology and histology.