Whole-genome long-read TAPS deciphers DNA methylation patterns at base resolution using PacBio SMRT sequencing technology

Research progress and application of the third-generation sequencing technologies in forensic medicine

Third-generation sequencing technologies, exemplified by single-molecule real-time sequencing and nanopore sequencing, provide a constellation of advantages, including long read lengths, high throughput, real-time sequencing capabilities, and remarkable portability. These cutting-edge methodologies have provided new tools for genomic analysis in forensic medicine. To gain a comprehensive understanding of the current applications and cutting-edge trends of third-generation sequencing technologies in forensic medicine, this study retrieved relevant literature from the China National Knowledge Infrastructure (CNKI) database and the Web of Science (WOS) database. Using bibliometric software CiteSpace 6.1.R6, the study visualized publication volume, countries, and keywords related to the application of third-generation sequencing technologies in forensic medicine from 2014 to 2023. The review then summarized the foundational principles, characteristics, and promising prospects of third-generation sequencing technologies in forensic medicine. Notably, it highlights their remarkable contributions in forensic individual identification, body fluid identification, forensic epigenetic analysis, microbial analysis and forensic species identification.

Full-Length Immune Repertoire Reconstruction and Profiling at the Transcriptome Level Using Long-Read Sequencing

BACKGROUND

Due to the diversity of the immune repertoire (IR), reconstructing full-length IR using traditional short-read sequencing has proven challenging.

METHODS

A full-length IR sequencing (FLIRseq) work flow was developed with linear rolling circle amplification and nanopore sequencing. Its accuracy and quantification ability were verified by plasmid mixtures and commercial B-cell receptor/T-cell receptor sequencing (BCR/TCR-seq) based on short reads. IRs in tissues and the peripheral blood from 8 patients with acute lymphoblastic leukemia, 3 patients with allergic diseases, 4 patients with psoriasis, and 5 patients with prostate cancer were analyzed using FLIRseq.

RESULTS

FLIRseq reads had lower mismatch rates and gap rates, and higher identify rates than nanopore reads (all P < 2.2 × -16). The relative quantification of components by FLIRseq was consistent with the actual quantification (P > 0.05). FLIRseq had superiority over BCR/TCR-seq, providing the long complementarity-determining region 3, B-cell isotype, and the rarely used V gene sequence. FLIRseq observed an increase in clonotype diversity (P < 0.05) and a decrease in the percentage of abnormal BCRs/TCRs in patients with leukemia in remission. For patients with allergic diseases or psoriasis, FLIRseq provided direct insights into V(D)J recombination and specific immunoglobulin classes. Compared with that in prostate cancer tissues, the full-length V segment of the biased T-cell receptor β chain from lymphocytes in psoriatic tissues showed a more consistent AlphaFold2-predicted protein structure (P < 0.05).

CONCLUSIONS

FLIRseq enables unbiased and comprehensive analyses of direct V(D)J recombination and immunoglobulin classes, thereby contributing to characterizing pathogenic mechanisms, monitoring minimal residual disease, and customizing adoptive cell therapy.

Local read haplotagging enables accurate long-read small variant calling

Long-read sequencing technology has enabled variant detection in difficult-to-map regions of the genome and enabled rapid genetic diagnosis in clinical settings. Rapidly evolving third-generation sequencing platforms like Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT) are introducing newer platforms and data types. It has been demonstrated that variant calling methods based on deep neural networks can use local haplotyping information with long-reads to improve the genotyping accuracy. However, using local haplotype information creates an overhead as variant calling needs to be performed multiple times which ultimately makes it difficult to extend to new data types and platforms as they get introduced. In this work, we have developed a local haplotype approximate method that enables state-of-the-art variant calling performance with multiple sequencing platforms including PacBio Revio system, ONT R10.4 simplex and duplex data. This addition of local haplotype approximation simplifies long-read variant calling with DeepVariant.

Single-nucleoid architecture reveals heterogeneous packaging of mitochondrial DNA

Cellular metabolism relies on the regulation and maintenance of mitochondrial DNA (mtDNA). Hundreds to thousands of copies of mtDNA exist in each cell, yet because mitochondria lack histones or other machinery important for nuclear genome compaction, it remains unresolved how mtDNA is packaged into individual nucleoids. In this study, we used long-read single-molecule accessibility mapping to measure the compaction of individual full-length mtDNA molecules at near single-nucleotide resolution. We found that, unlike the nuclear genome, human mtDNA largely undergoes all-or-none global compaction, with most nucleoids existing in an inaccessible, inactive state. Highly accessible mitochondrial nucleoids are co-occupied by transcription and replication components and selectively form a triple-stranded displacement loop structure. In addition, we showed that the primary nucleoid-associated protein TFAM directly modulates the fraction of inaccessible nucleoids both in vivo and in vitro, acting consistently with a nucleation-and-spreading mechanism to coat and compact mitochondrial nucleoids. Together, these findings reveal the primary architecture of mtDNA packaging and regulation in human cells.

Circulating cell-free DNA-based methylation pattern in plasma for early diagnosis of esophagus cancer

With the increased awareness of early tumor detection, the importance of detecting and diagnosing esophageal cancer in its early stages has been underscored. Studies have consistently demonstrated the crucial role of methylation levels in circulating cell-free DNA (cfDNA) in identifying and diagnosing early-stage cancer. cfDNA methylation pertains to the methylation state within the genomic scope of cfDNA and is strongly associated with cancer development and progression. Several research teams have delved into the potential application of cfDNA methylation in identifying early-stage esophageal cancer and have achieved promising outcomes. Recent research supports the high sensitivity and specificity of cfDNA methylation in early esophageal cancer diagnosis, providing a more accurate and efficient approach for early detection and improved clinical management. Accordingly, this review aims to present an overview of methylation-based cfDNA research with a focus on the latest developments in the early detection of esophageal cancer. Additionally, this review summarizes advanced analytical technologies for cfDNA methylation that have significantly benefited from recent advancements in separation and detection techniques, such as methylated DNA immunoprecipitation sequencing (MeDIP-seq). Recent findings suggest that biomarkers based on cfDNA methylation may soon find successful applications in the early detection of esophageal cancer. However, large-scale prospective clinical trials are required to identify the potential of these biomarkers.

Local read haplotagging enables accurate long-read small variant calling

Long-read sequencing technology has enabled variant detection in difficult-to-map regions of the genome and enabled rapid genetic diagnosis in clinical settings. Rapidly evolving third-generation sequencing platforms like Pacific Biosciences (PacBio) and Oxford nanopore technologies (ONT) are introducing newer platforms and data types. It has been demonstrated that variant calling methods based on deep neural networks can use local haplotyping information with long-reads to improve the genotyping accuracy. However, using local haplotype information creates an overhead as variant calling needs to be performed multiple times which ultimately makes it difficult to extend to new data types and platforms as they get introduced. In this work, we have developed a local haplotype approximate method that enables state-of-the-art variant calling performance with multiple sequencing platforms including PacBio Revio system, ONT R10.4 simplex and duplex data. This addition of local haplotype approximation makes DeepVariant a universal variant calling solution for long-read sequencing platforms.

Mapping epigenetic modifications by sequencing technologies

The "epigenetics" concept was first described in 1942. Thus far, chemical modifications on histones, DNA, and RNA have emerged as three important building blocks of epigenetic modifications. Many epigenetic modifications have been intensively studied and found to be involved in most essential biological processes as well as human diseases, including cancer. Precisely and quantitatively mapping over 100 [1], 17 [2], and 160 [3] different known types of epigenetic modifications in histone, DNA, and RNA is the key to understanding the role of epigenetic modifications in gene regulation in diverse biological processes. With the rapid development of sequencing technologies, scientists are able to detect specific epigenetic modifications with various quantitative, high-resolution, whole-genome/transcriptome approaches. Here, we summarize recent advances in epigenetic modification sequencing technologies, focusing on major histone, DNA, and RNA modifications in mammalian cells.

A tool for rapid, automated characterization of population epigenomics in plants

Epigenetic variation in plant populations is an important factor in determining phenotype and adaptation to the environment. However, while advances have been made in the molecular and computational methods to analyze the methylation status of a given sample of DNA, tools to profile and compare the methylomes of multiple individual plants or groups of plants at high resolution and low cost are lacking. Here, we describe a computational approach and R package (sounDMR) that leverages the benefits of long read nanopore sequencing to enable robust identification of differential methylation from complex experimental designs, as well as assess the variability within treatment groups and identify individual plants of interest. We demonstrate the utility of this approach by profiling a population of Arabidopsis thaliana exposed to a demethylating agent and identify genomic regions of high epigenetic variability between individuals. Given the low cost of nanopore sequencing devices and the ease of sample preparation, these results show that high resolution epigenetic profiling of plant populations can be made more broadly accessible in plant breeding and biotechnology.

The Integration of Data from Different Long-Read Sequencing Platforms Enhances Proteoform Characterization in Arabidopsis

The increasing availability of massive omics data requires improving the quality of reference databases and their annotations. The combination of full-length isoform sequencing (Iso-Seq) with short-read transcriptomics and proteomics has been successfully used for increasing proteoform characterization, which is a main ongoing goal in biology. However, the potential of including Oxford Nanopore Technologies Direct RNA Sequencing (ONT-DRS) data has not been explored. In this paper, we analyzed the impact of combining Iso-Seq- and ONT-DRS-derived data on the identification of proteoforms in Arabidopsis MS proteomics data. To this end, we selected a proteomics dataset corresponding to senescent leaves and we performed protein searches using three different protein databases: AtRTD2 and AtRTD3, built from the homonymous transcriptomes, regarded as the most complete and up-to-date available for the species; and a custom hybrid database combining AtRTD3 with publicly available ONT-DRS transcriptomics data generated from Arabidopsis leaves. Our results show that the inclusion and combination of long-read sequencing data from Iso-Seq and ONT-DRS into a proteogenomic workflow enhances proteoform characterization and discovery in bottom-up proteomics studies. This represents a great opportunity to further investigate biological systems at an unprecedented scale, although it brings challenges to current protein searching algorithms.

Bacterial DNA methyltransferase: A key to the epigenetic world with lessons learned from proteobacteria

Epigenetics modulates expression levels of various important genes in both prokaryotes and eukaryotes. These epigenetic traits are heritable without any change in genetic DNA sequences. DNA methylation is a universal mechanism of epigenetic regulation in all kingdoms of life. In bacteria, DNA methylation is the main form of epigenetic regulation and plays important roles in affecting clinically relevant phenotypes, such as virulence, host colonization, sporulation, biofilm formation et al. In this review, we survey bacterial epigenomic studies and focus on the recent developments in the structure, function, and mechanism of several highly conserved bacterial DNA methylases. These methyltransferases are relatively common in bacteria and participate in the regulation of gene expression and chromosomal DNA replication and repair control. Recent advances in sequencing techniques capable of detecting methylation signals have enabled the characterization of genome-wide epigenetic regulation. With their involvement in critical cellular processes, these highly conserved DNA methyltransferases may emerge as promising targets for developing novel epigenetic inhibitors for biomedical applications.