SMOOTH-seq: single-cell genome sequencing of human cells on a third-generation sequencing platform.
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ABSTRACT:
SUBMITTER: Fan X
PROVIDER: S-EPMC8247186 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description: Not available
| S-EPMC9834245 | biostudies-literature
Project description:The development of next generation sequencing (NGS) platform-based single-cell RNA sequencing (scRNA-seq) techniques has tremendously changed biological researches, while there are still many questions that cannot be addressed by them due to their short read lengths. We developed a novel scRNA-seq technology based on third-generation sequencing (TGS) platform (single-cell amplification and sequencing of full-length RNAs by Nanopore platform, SCAN-seq). SCAN-seq exhibited high sensitivity and accuracy comparable to NGS platform-based scRNA-seq methods. Moreover, we captured thousands of unannotated transcripts of diverse types, with high verification rate by reverse transcription PCR (RT-PCR)-coupled Sanger sequencing in mouse embryonic stem cells (mESCs). Then, we used SCAN-seq to analyze the mouse preimplantation embryos. We could clearly distinguish cells at different developmental stages, and a total of 27,250 unannotated transcripts from 9,338 genes were identified, with many of which showed developmental stage-specific expression patterns. Finally, we showed that SCAN-seq exhibited high accuracy on determining allele-specific gene expression patterns within an individual cell. SCAN-seq makes a major breakthrough for single-cell transcriptome analysis field.
| S-EPMC7773192 | biostudies-literature
Project description:Restriction-enzyme (RE)-based next-generation sequencing methods have revolutionized marker-assisted genetic studies; however, the use of REs has limited their widespread adoption, especially in field samples with low-quality DNA and/or small quantities of DNA. Here, we developed a PCR-based procedure to construct reduced representation libraries without RE digestion steps, representing de novo single-nucleotide polymorphism discovery, and its genotyping using next-generation sequencing. Using multiplexed inter-simple sequence repeat (ISSR) primers, thousands of genome-wide regions were amplified effectively from a wide variety of genomes, without prior genetic information. We demonstrated: 1) Mendelian gametic segregation of the discovered variants; 2) reproducibility of genotyping by checking its applicability for individual identification; and 3) applicability in a wide variety of species by checking standard population genetic analysis. This approach, called multiplexed ISSR genotyping by sequencing, should be applicable to many marker-assisted genetic studies with a wide range of DNA qualities and quantities.
| S-EPMC4655332 | biostudies-literature
Project description:Since the first description of a commensal seminal microbiome using sequencing, less than a decade ago, interest in the composition of this microbiome and its relationship with fertility has been growing. Articles using next-generation sequencing techniques agree on the identification of the most abundant bacterial phyla. However, at the genus level, there is still no consensus on which bacteria are most abundant in human seminal plasma. This discrepancy may be due to methodological variability such as sample collection, bacterial DNA extraction methodology, which hypervariable regions of 16S rRNA gene have been amplified, or bioinformatic analysis. In the present work, seminal microbiota of 14 control samples and 42 samples of idiopathic infertile patients were characterized based on full-length sequencing of the 16S rRNA gene using MinION platform from Oxford Nanopore. These same samples had been analyzed previously using Illumina's MiSeq sequencing platform. Comparison between the results obtained with the two platforms has been used to analyze the impact of sequencing method on the study of the seminal microbiome's composition. Seminal microbiota observed with MinION were mainly composed of the phyla Firmicutes, Proteobacteria, Bacteroidetes and Actinobacteria, with the most abundant genera being Peptoniphilus, Finegoldia, Staphylococcus, Anaerococcus, Campylobacter, Prevotella, Streptococcus, Lactobacillus, Ezakiella and Enterococcus. This composition was similar to that found by the Illumina platform, since these 10 most abundant genera were also among the most abundant genera detected by the Nanopore platform. In both cases, the top 10 genera represented more than 70% of the classified reads. However, relative abundance of each bacterium did not correlate between these two platforms, with intraindividual variations of up to 50 percentage points in some cases. Results suggest that the effect of the sequencing platform on the characterization of seminal microbiota is not very large at the phylum level, with slightly variances in Firmicutes and Actinobacteria, but presents differences at the genus level. These differences could alter the composition and diversity of bacterial profiles or posterior analyses. This indicates the importance of conducting multi-platform studies to better characterize seminal microbioma.
| S-EPMC10178615 | biostudies-literature
Project description:Human gut microbiota modulates normal physiological functions, such as maintenance of barrier homeostasis and modulation of metabolism, as well as various chronic diseases including type 2 diabetes and gastrointestinal cancer. Despite decades of research, the composition of the gut microbiota remains poorly understood. Here, we established an effective extraction method to obtain high quality gut microbiota genomes, and analyzed them with third-generation sequencing technology. We acquired a large quantity of data from each sample and assembled large numbers of reliable contigs. With this approach, we constructed tens of completed bacterial genomes in which there were several new bacteria species. We also identified a new conditional pathogen, Enterococcus tongjius, which is a member of Enterococci. This work provided a novel and reliable approach to recover gut microbiota genomes, facilitating the discovery of new bacteria species and furthering our understanding of the microbiome that underlies human health and diseases.
| S-EPMC8172872 | biostudies-literature
Project description:We developed SCAN-seq2, a high-throughput and highly sensitive single-cell RNA sequencing method based on the TGS platform. Our study demonstrated that SCAN-seq2 improves upon the previous method, SCAN-seq, in terms of sensitivity and throughput. By using reference-guided assembly of single-cell data, we were able to identify thousands of novel full-length RNA isoforms, including cell type-specific expression patterns of pseudogenes. We also accurately determined V(D)J rearrangement events in T and B cells. Lastly, we found that treatment of HepG2 and Hela cells with the spliceosome inhibitor Isoginkgetin (IGG) resulted in a subpopulation of cells with distinct apoptosis features. Our study provides a promising new tool for single-cell transcriptome research. The source code for SCAN-seq2 data analysis pipelines is available at https://github.com/liuzhenyu-yyy/SCAN-seq2 .
2022-11-15 | GSE203561 | GEO
Project description:MotivationRNA viruses tend to mutate constantly. While many of the variants are neutral, some can lead to higher transmissibility or virulence. Accurate assembly of complete viral genomes enables the identification of underlying variants, which are essential for studying virus evolution and elucidating the relationship between genotypes and virus properties. Recently, third-generation sequencing platforms such as Nanopore sequencers have been used for real-time virus sequencing for Ebola, Zika, coronavirus disease 2019, etc. However, their high per-base error rate prevents the accurate reconstruction of the viral genome.ResultsIn this work, we introduce a new tool, AccuVIR, for viral genome assembly and polishing using error-prone long reads. It can better distinguish sequencing errors from true variants based on the key observation that sequencing errors can disrupt the gene structures of viruses, which usually have a high density of coding regions. Our experimental results on both simulated and real third-generation sequencing data demonstrated its superior performance on generating more accurate viral genomes than generic assembly or polish tools.Availability and implementationThe source code and the documentation of AccuVIR are available at https://github.com/rainyrubyzhou/AccuVIR.Supplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC9825286 | biostudies-literature
Project description:Accurate detection of variants and long-range haplotypes in genomes of single human cells remains very challenging. Common approaches require extensive in vitro amplification of genomes of individual cells using DNA polymerases and high-throughput short-read DNA sequencing. These approaches have two notable drawbacks. First, polymerase replication errors could generate tens of thousands of false-positive calls per genome. Second, relatively short sequence reads contain little to no haplotype information. Here we report a method, which is dubbed SISSOR (single-stranded sequencing using microfluidic reactors), for accurate single-cell genome sequencing and haplotyping. A microfluidic processor is used to separate the Watson and Crick strands of the double-stranded chromosomal DNA in a single cell and to randomly partition megabase-size DNA strands into multiple nanoliter compartments for amplification and construction of barcoded libraries for sequencing. The separation and partitioning of large single-stranded DNA fragments of the homologous chromosome pairs allows for the independent sequencing of each of the complementary and homologous strands. This enables the assembly of long haplotypes and reduction of sequence errors by using the redundant sequence information and haplotype-based error removal. We demonstrated the ability to sequence single-cell genomes with error rates as low as 10-8 and average 500-kb-long DNA fragments that can be assembled into haplotype contigs with N50 greater than 7 Mb. The performance could be further improved with more uniform amplification and more accurate sequence alignment. The ability to obtain accurate genome sequences and haplotype information from single cells will enable applications of genome sequencing for diverse clinical needs.
| S-EPMC5703283 | biostudies-literature
Project description:Recent analyses show that transcriptome sequencing can be utilized as a diagnostic tool for rare Mendelian diseases. The third generation sequencing de novo detects long reads of thousands of base pairs, thus greatly expanding the isoform discovery and identification of novel long noncoding RNAs. In this study, we developed TGStools, a bioinformatics suite to facilitate routine tasks such as characterizing full-length transcripts, detecting shifted types of alternative splicing, and long noncoding RNAs (lncRNAs) identification in transcriptome analysis. It also prioritizes the transcripts with a visualization framework that automatically integrates rich annotation with known genomic features. TGStools is a Python package freely available at Github.
| S-EPMC6678717 | biostudies-literature
Project description:IntroductionMycobacterial diseases are a significant source of disease burden, with Mycobacterium tuberculosis being the most common infectious cause of death worldwide. Given this, the emergence of antibiotic resistance in these species is of particular interest. By examining the epidemiology of mycobacteria in humans and cattle in an area of intense human-animal contact (the Ugandan cattle corridor [UCC]) and using a novel whole-genome sequencing technique to analyse organism diversity, this study will explore the role bidirectional transmission of mycobacteria plays in the local ecology, as well the significance of zoonotic Mycobacterium bovis in the human population.Methods and analysisThis ongoing study includes both a cross-sectional analysis of the UCC mycobacteria-positive population and novel laboratory-based research focused on differentiating the species causing M. tuberculosis complex-linked disease. We will use a third-generation sequencing platform (the MinION sequencer from Oxford Nanopore Technology), comparing data from a sample subset to the Illumina platform as a means of measuring viability of the MinION platform in this specific setting. Our full sample set will be sequenced on Illumina and the data will be used to perform epidemiological and phylogenetic analyses.Ethics and disseminationEthical approval was obtained from both the University of Minnesota IRB committee and the Ugandan National Council for Science and Technology-Research Ethics Committee. Samples were obtained after patients signed an informed consent indicating samples could be retained and used for research purposes. All samples are deidentified, with only basic demographic and geographic information being retained per national tuberculosis (TB) recording guidelines. Significant drug resistance results will be referred back to the local TB control officer to inform patient care. Final results of the study will be submitted to infectious disease-specific journals and will be submitted to the annual Infectious Diseases Society of America (IDSA) meeting.
| S-EPMC6500349 | biostudies-literature