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  1. ...information. A similar challenge arises in transcriptomics in which multiple sequencing reads need to be aggregated into a single transcript abundance. Probabilistic tools, such as RNA-seq by expectation maximization (RSEM) (Li and Dewey 2011), have provided effective transcript aggregation. However, protein...
  2. ...intensive and equipment dependent and requires highly skilled technicians; thus, to maximize the efficiency, we designed a high-input/low-output pooled strategy (Fig. 1A). As in the pooled strategy, the target gene of an individual mutant is indicated by the integrated single-guide RNA (sgRNA) sequence...
  3. ...structure analyses, genetic diversity evaluation, and ancestry estimation (Kennedy et al. 2003; Zimmerman et al. 2020). Simultaneously, the latest advances in SNP high-throughput arrays and WGS facilitate the SNPs applied in the usual genetic analyses. However, compared with WGS, SNP arrays were primarily...
  4. ...-Iseppi et al. 2021). In our study, we developed a workflow designed to streamline the analysis aspect of high-throughput long-read RNA sequencing data, enabling the identification of transcript isoforms at the single-cell level. Our workflow modified the 10x Genomics scRNA-seq protocol (Gupta et al. 2018...
  5. ...) devider haplotypes from an ONT R10.4 16S rRNA data set for the reference 16S sequence of the most abundant species Massilia burnea. (E) Phylogenetic tree of haplotypes assigned to the M. burnea reference. Depth of coverage is shown next to the haplotype ID. The x-axis shows the branch length from the root...
  6. ...of Pharmaceutical Biotechnology and Department of Medicine, the University of Hong Kong, Hong Kong SAR, China ↵9 These authors contributed equally to this work. Corresponding authors: su@chemie.uni-siegen.de, zhouxm@scnu.edu.cn, qz.lian@siat.ac.cnAbstractRNA sequencing (RNA-seq) is a pivotal tool for transcriptomic...
  7. ...), and the development of microarrays first (Schena et al. 1995) and high-throughput sequencing later (Margulies et al. 2005) boosted our capacity to analyze transcriptomes. Nowadays, the most common technique to analyze gene expression is RNA sequencing (RNA-seq). This technique consists of first isolating RNA from...
  8. ...ligated into the expression cassettes of the CRISPR-Cas9 (Supplemental Fig. S1B). To evaluate the quality, total sgRNAs amplified from the pooled plasmids were sequenced by high-throughput sequencing (HTS). These results showed that 89.74% of the sgRNA (16,228) read counts fell into the range between one...
  9. ...in pancreatic cancer tumors, while also being essential for pancreatic cancer cell proliferation. Using comparative nanopore direct RNA sequencing, we identify potential METTL2A-mediated m3C sites in poly(A) RNA. These m3C sites are mapped in both messenger RNA and mitochondrial RNA and are enriched in the CC...
  10. ...normal samples, subsequently integrating them to reconstruct the samples’ clonal heterogeneity, and identifying subclones with different predicted treatment outcomes.ResultsOverview of LongSom, a computational workflow for LR scRNA-seq variant detection and clonal reconstructionWe developed Long...
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