scholarly journals Pattern of Repetitive Element Transcription Segregate Cell Lineages during the Embryogenesis of Sea Urchin Strongylocentrotus purpuratus

Biomedicines ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1736
Author(s):  
Nick Panyushev ◽  
Larisa Okorokova ◽  
Lavrentii Danilov ◽  
Leonid Adonin
Keyword(s):  
Single Cell ◽  
Sea Urchin ◽  
De Novo ◽  
Transcriptome Assembly ◽  
Strongylocentrotus Purpuratus ◽  
Sequencing Data ◽  
Cell Lineages ◽  
Mesenchyme Cell ◽  
Resolution Level ◽  
Developmental Domains

Repetitive elements (REs) occupy a significant part of eukaryotic genomes and are shown to play diverse roles in genome regulation. During embryogenesis of the sea urchin, a large number of REs are expressed, but the role of these elements in the regulation of biological processes remains unknown. The aim of this study was to identify the RE expression at different stages of embryogenesis. REs occupied 44% of genomic DNA of Strongylocentrotus purpuratus. The most prevalent among these elements were the unknown elements—in total, they contributed 78.5% of REs (35% in total genome occupancy). It was revealed that the transcription pattern of genes and REs changes significantly during gastrulation. Using the de novo transcriptome assembly, we showed that the expression of RE is independent of its copy number in the genome. We also identified copies that are expressed. Only active RE copies were used for mapping and quantification of RE expression in the single-cell RNA sequencing data. REs expression was observed in all cell lineages and they were detected as population markers. Moreover, the primary mesenchyme cell (PMC) line had the greatest diversity of REs among the markers. Our data suggest a role for RE in the organization of developmental domains during the sea urchin embryogenesis at the single-cell resolution level.

scholarly journals Multi-regional characterisation of renal cell carcinoma and microenvironment at single cell resolution

2021 ◽  
Author(s):  
Ruoyan Li ◽  
John R. Ferdinand ◽  
Kevin W. Loudon ◽  
Georgina S. Bowyer ◽  
Lira Mamanova ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Function ◽  
De Novo ◽  
Epithelial Mesenchymal Transition ◽  
Spatial Location ◽  
De Novo Mutation ◽  
Cellular Interactions ◽  
Sequencing Data ◽  
Mesenchymal Transition ◽  
Multiple Regions

Tumour behaviour is dependent on the oncogenic properties of cancer cells and their multi-cellular interactions. These dependencies were examined through 270,000 single cell transcriptomes and 100 micro-dissected whole exomes obtained from 12 patients with kidney tumours. Tissue was sampled from multiple regions of tumour core, tumour-normal interface, normal surrounding tissues, and peripheral blood. We found the principal spatial location of CD8+ T cell clonotypes largely defined exhaustion state, with clonotypic heterogeneity not explained by somatic intra-tumoural heterogeneity. De novo mutation calling from single cell RNA sequencing data allows us to lineage-trace and infer clonality of cells. We discovered six meta-programmes that distinguish tumour cell function. An epithelial-mesenchymal transition meta-programme, enriched at the tumour-normal interface appears modulated through macrophage expressed IL1B, potentially forming a therapeutic target.

scholarly journals Fully phased human genome assembly without parental data using single-cell strand sequencing and long reads

2020 ◽  
Author(s):  
David Porubsky ◽  
◽  
Peter Ebert ◽  
Peter A. Audano ◽  
Mitchell R. Vollger ◽  
...  
Keyword(s):  
Single Cell ◽  
Genome Assembly ◽  
De Novo ◽  
Error Rates ◽  
Sequencing Data ◽  
Single Nucleotide Variants ◽  
De Novo Genome Assembly ◽  
Parental Data ◽  
Human Genome Assembly ◽  
Long Read

AbstractHuman genomes are typically assembled as consensus sequences that lack information on parental haplotypes. Here we describe a reference-free workflow for diploid de novo genome assembly that combines the chromosome-wide phasing and scaffolding capabilities of single-cell strand sequencing1,2 with continuous long-read or high-fidelity3 sequencing data. Employing this strategy, we produced a completely phased de novo genome assembly for each haplotype of an individual of Puerto Rican descent (HG00733) in the absence of parental data. The assemblies are accurate (quality value > 40) and highly contiguous (contig N50 > 23 Mbp) with low switch error rates (0.17%), providing fully phased single-nucleotide variants, indels and structural variants. A comparison of Oxford Nanopore Technologies and Pacific Biosciences phased assemblies identified 154 regions that are preferential sites of contig breaks, irrespective of sequencing technology or phasing algorithms.

Computational Approaches for Transcriptome Assembly Based on Sequencing Technologies

2020 ◽  
Vol 15 (1) ◽  
pp. 2-16
Author(s):  
Yuwen Luo ◽  
Xingyu Liao ◽  
Fang-Xiang Wu ◽  
Jianxin Wang
Keyword(s):  
De Novo ◽  
Transcriptome Assembly ◽  
Critical Role ◽  
High Sensitivity ◽  
Biological Properties ◽  
Sequencing Data ◽  
Sequencing Technologies ◽  
Long Reads ◽  
Massive Sequencing ◽  
Generation Sequencing

Transcriptome assembly plays a critical role in studying biological properties and examining the expression levels of genomes in specific cells. It is also the basis of many downstream analyses. With the increase of speed and the decrease in cost, massive sequencing data continues to accumulate. A large number of assembly strategies based on different computational methods and experiments have been developed. How to efficiently perform transcriptome assembly with high sensitivity and accuracy becomes a key issue. In this work, the issues with transcriptome assembly are explored based on different sequencing technologies. Specifically, transcriptome assemblies with next-generation sequencing reads are divided into reference-based assemblies and de novo assemblies. The examples of different species are used to illustrate that long reads produced by the third-generation sequencing technologies can cover fulllength transcripts without assemblies. In addition, different transcriptome assemblies using the Hybrid-seq methods and other tools are also summarized. Finally, we discuss the future directions of transcriptome assemblies.

scholarly journals Exploring cell-specific miRNA regulation with single-cell miRNA-mRNA co-sequencing data

2020 ◽  
Author(s):  
Junpeng Zhang ◽  
Lin Liu ◽  
Taosheng Xu ◽  
Wu Zhang ◽  
Chunwen Zhao ◽  
...  
Keyword(s):  
Single Cell ◽  
Regulatory Networks ◽  
Single Cells ◽  
Small Scale ◽  
Mirna Regulation ◽  
Sequencing Data ◽  
Resolution Level ◽  
Novel Strategy ◽  
Cell Cell

AbstractBackgroundExisting computational methods for studying miRNA regulation are mostly based on bulk miRNA and mRNA expression data. However, bulk data only allows the analysis of miRNA regulation regarding a group of cells, rather than the miRNA regulation unique to individual cells. Recent advance in single-cell miRNA-mRNA co-sequencing technology has opened a way for investigating miRNA regulation at single-cell level. However, as currently single-cell miRNA-mRNA co-sequencing data is just emerging and only available at small-scale, there is a strong need of novel methods to exploit existing single-cell data for the study of cell-specific miRNA regulation.ResultsIn this work, we propose a new method, CSmiR (Cell-Specific miRNA regulation) to use single-cell miRNA-mRNA co-sequencing data to identify miRNA regulatory networks at the resolution of individual cells. We apply CSmiR to the miRNA-mRNA co-sequencing data in 19 K562 single-cells to identify cell-specific miRNA-mRNA regulatory networks to understand miRNA regulation in each K562 single-cell. By analyzing the obtained cell-specific miRNA-mRNA regulatory networks, we observe that the miRNA regulation in each K562 single-cell is unique. Moreover, we conduct detailed analysis on the cell-specific miRNA regulation associated with the miR-17/92 family as a case study. Finally, through exploring cell-cell similarity matrix characterized by cell-specific miRNA regulation, CSmiR provides a novel strategy for clustering single-cells to help understand cell-cell crosstalk.ConclusionsTo the best of our knowledge, CSmiR is the first method to explore miRNA regulation at a single-cell resolution level, and we believe that it can be a useful method to enhance the understanding of cell-specific miRNA regulation.

scholarly journals Raw transcriptomics data to gene specific SSRs: a validated free bioinformatics workflow for biologists

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
D. N. U. Naranpanawa ◽  
C. H. W. M. R. B. Chandrasekara ◽  
P. C. G. Bandaranayake ◽  
A. U. Bandaranayake
Keyword(s):  
De Novo ◽  
Sequence Data ◽  
Transcriptome Assembly ◽  
Low Cost ◽  
Santalum Album ◽  
Sequencing Data ◽  
Illumina Hiseq ◽  
Tissue Samples ◽  
Downstream Analysis ◽  
Bioinformatics Workflow

Abstract Recent advances in next-generation sequencing technologies have paved the path for a considerable amount of sequencing data at a relatively low cost. This has revolutionized the genomics and transcriptomics studies. However, different challenges are now created in handling such data with available bioinformatics platforms both in assembly and downstream analysis performed in order to infer correct biological meaning. Though there are a handful of commercial software and tools for some of the procedures, cost of such tools has made them prohibitive for most research laboratories. While individual open-source or free software tools are available for most of the bioinformatics applications, those components usually operate standalone and are not combined for a user-friendly workflow. Therefore, beginners in bioinformatics might find analysis procedures starting from raw sequence data too complicated and time-consuming with the associated learning-curve. Here, we outline a procedure for de novo transcriptome assembly and Simple Sequence Repeats (SSR) primer design solely based on tools that are available online for free use. For validation of the developed workflow, we used Illumina HiSeq reads of different tissue samples of Santalum album (sandalwood), generated from a previous transcriptomics project. A portion of the designed primers were tested in the lab with relevant samples and all of them successfully amplified the targeted regions. The presented bioinformatics workflow can accurately assemble quality transcriptomes and develop gene specific SSRs. Beginner biologists and researchers in bioinformatics can easily utilize this workflow for research purposes.

scholarly journals TedSim: temporal d​ynamics sim​ulation of single cell RNA-sequencing data and cell division history

2021 ◽  
Author(s):  
Xinhai Pan ◽  
Hechen Li ◽  
Xiuwei Zhang
Keyword(s):  
Cell Division ◽  
Single Cell ◽  
Genome Editing ◽  
Computational Methods ◽  
Temporal Dynamics ◽  
Cell Types ◽  
Sequencing Data ◽  
Gene Expressions ◽  
Cell Lineages ◽  
Multiple Cell

Recently, the combined scRNA-seq and CRISPR/Cas9 genome editing technologies have enabled simultaneous readouts of gene expressions and lineage barcodes, which allows for the reconstruction of the cell division tree, and makes it possible to trace the origin of each cell type. Computational methods are emerging to take advantage of the jointly profiled scRNA-seq and lineage barcode data to better reconstruct the cell division history or to infer the cell state trajectories. Here, we present TedSim (single cell Temporal dynamics Simulator), a simulator that simulates the cell division events from the root cell to present-day cells, simultaneously generating the CRISPR/Cas9 genome editing lineage barcodes and scRNA-seq data. In particular, TedSim generates cells from multiple cell types through cell division events. TedSim can be used to benchmark and investigate computational methods which use either or both of the two types of data, scRNA-seq and lineage barcodes, to study cell lineages or trajectories. TedSim is available at: https://github.com/Galaxeee/TedSim.

scholarly journals PAHs and PCBs Affect Functionally Intercorrelated Genes in the Sea Urchin Paracentrotus lividus Embryos

2021 ◽  
Vol 22 (22) ◽  
pp. 12498
Author(s):  
Luisa Albarano ◽  
Valerio Zupo ◽  
Marco Guida ◽  
Giovanni Libralato ◽  
Davide Caramiello ◽  
...  
Keyword(s):  
Real Time ◽  
Sea Urchin ◽  
Sublethal Effects ◽  
De Novo ◽  
Transcriptome Assembly ◽  
Molecular Targets ◽  
Paracentrotus Lividus ◽  
Marine Biota ◽  
New Genes ◽  
Real Time Qpcr

Polycyclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs) represent the most common pollutants in the marine sediments. Previous investigations demonstrated short-term sublethal effects of sediments polluted with both contaminants on the sea urchin Paracentrotus lividus after 2 months of exposure in mesocosms. In particular, morphological malformations observed in P. lividus embryos deriving from adults exposed to PAHs and PCBs were explained at molecular levels by de novo transcriptome assembly and real-time qPCR, leading to the identification of several differentially expressed genes involved in key physiological processes. Here, we extensively explored the genes involved in the response of the sea urchin P. lividus to PAHs and PCBs. Firstly, 25 new genes were identified and interactomic analysis revealed that they were functionally connected among them and to several genes previously defined as molecular targets of response to the two pollutants under analysis. The expression levels of these 25 genes were followed by Real Time qPCR, showing that almost all genes analyzed were affected by PAHs and PCBs. These findings represent an important further step in defining the impacts of slight concentrations of such contaminants on sea urchins and, more in general, on marine biota, increasing our knowledge of molecular targets involved in responses to environmental stressors.

scholarly journals A de novo Transcriptome Assembly of the European Flounder (Platichthys flesus): The Preselection of Transcripts Encoding Active Forms of Enzymes

2021 ◽  
Vol 8 ◽  
Author(s):  
Konrad Pomianowski ◽  
Artur Burzyński ◽  
Ewa Kulczykowska
Keyword(s):  
De Novo ◽  
Transcriptome Assembly ◽  
Head Kidney ◽  
Sequencing Data ◽  
Mrna Isoforms ◽  
Protein Database ◽  
Next Generation Sequencing Technology ◽  
Platichthys Flesus ◽  
European Flounder ◽  
High Level

The RNA sequencing data sets available for different fish species show a potentially high variety of forms of enzymes just in teleosts. This is primarily considered an effect of the first round of whole-genome duplication with mutations in duplicated genes (isozymes) and alternative splicing of mRNA (isoforms). However, the abundance of the mRNA transcript variants is not necessarily reflected in the abundance of active forms of proteins. We have investigated the transcriptional profiles of two enzymes, aralkylamine N-acetyltransferase (AANAT: EC 2.3.1.87) and N-acetylserotonin O-methyltransferase (ASMT: EC 2.1.1.4), in the eyeball, brain, intestines, spleen, heart, liver, head kidney, gonads, and skin of the European flounder (Platichthys flesus). High-throughput next-generation sequencing technology NovaSeq6000 was used to generate 500M sequencing reads. These were then assembled and filtered producing 75k reliable contigs. Gene ontology (GO) terms were assigned to the majority of annotated contigs/unigenes based on the results of PFAM, PANTHER, UniProt, and InterPro protein database searches. BUSCOs statistics for metazoa, vertebrata, and actinopterygii databases showed that the reported transcriptome represents a high level of completeness. In this article, we show how to preselect transcripts encoding the active enzymes (isozymes or isoforms), using AANAT and ASMT in the European flounder as the examples. The data can be used as a tool to design the experiments as well as a basis for discussion of diversity of enzyme forms and their physiological relevance in teleosts.

scholarly journals Exploring cell-specific miRNA regulation with single-cell miRNA-mRNA co-sequencing data

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Junpeng Zhang ◽  
Lin Liu ◽  
Taosheng Xu ◽  
Wu Zhang ◽  
Chunwen Zhao ◽  
...  
Keyword(s):  
Single Cell ◽  
Regulatory Networks ◽  
Single Cells ◽  
Small Scale ◽  
Mirna Regulation ◽  
Sequencing Data ◽  
Comparison Results ◽  
Resolution Level ◽  
Novel Strategy ◽  
Cell Cell

Abstract Background Existing computational methods for studying miRNA regulation are mostly based on bulk miRNA and mRNA expression data. However, bulk data only allows the analysis of miRNA regulation regarding a group of cells, rather than the miRNA regulation unique to individual cells. Recent advance in single-cell miRNA-mRNA co-sequencing technology has opened a way for investigating miRNA regulation at single-cell level. However, as currently single-cell miRNA-mRNA co-sequencing data is just emerging and only available at small-scale, there is a strong need of novel methods to exploit existing single-cell data for the study of cell-specific miRNA regulation. Results In this work, we propose a new method, CSmiR (Cell-Specific miRNA regulation) to combine single-cell miRNA-mRNA co-sequencing data and putative miRNA-mRNA binding information to identify miRNA regulatory networks at the resolution of individual cells. We apply CSmiR to the miRNA-mRNA co-sequencing data in 19 K562 single-cells to identify cell-specific miRNA-mRNA regulatory networks for understanding miRNA regulation in each K562 single-cell. By analyzing the obtained cell-specific miRNA-mRNA regulatory networks, we observe that the miRNA regulation in each K562 single-cell is unique. Moreover, we conduct detailed analysis on the cell-specific miRNA regulation associated with the miR-17/92 family as a case study. The comparison results indicate that CSmiR is effective in predicting cell-specific miRNA targets. Finally, through exploring cell–cell similarity matrix characterized by cell-specific miRNA regulation, CSmiR provides a novel strategy for clustering single-cells and helps to understand cell–cell crosstalk. Conclusions To the best of our knowledge, CSmiR is the first method to explore miRNA regulation at a single-cell resolution level, and we believe that it can be a useful method to enhance the understanding of cell-specific miRNA regulation.

scholarly journals ClusTrast: a short read de novo transcript isoform assembler guided by clustered contigs

2022 ◽  
Author(s):  
Karl Johan Westrin ◽  
Warren W Kretzschmar ◽  
Olof Emanuelsson
Keyword(s):  
Alternative Splicing ◽  
Reference Genome ◽  
De Novo ◽  
Transcriptome Assembly ◽  
Sequencing Data ◽  
Short Read ◽  
Transcript Isoforms ◽  
Short Reads ◽  
Moderate Reduction ◽  
Eukaryotic Species

Motivation: Transcriptome assembly from RNA sequencing data in species without a reliable reference genome has to be performed de novo, but studies have shown that de novo methods often have inadequate reconstruction ability of transcript isoforms. This impedes the study of alternative splicing, in particular for lowly expressed isoforms. Result: We present the de novo transcript isoform assembler ClusTrast, which clusters a set of guiding contigs by similarity, aligns short reads to the guiding contigs, and assembles each clustered set of short reads individually. We tested ClusTrast on datasets from six eukaryotic species, and showed that ClusTrast reconstructed more expressed known isoforms than any of the other tested de novo assemblers, at a moderate reduction in precision. An appreciable fraction were reconstructed to at least 95% of their length. We suggest that ClusTrast will be useful for studying alternative splicing in the absence of a reference genome. Availability and implementation: The code and usage instructions are available at https://github.com/karljohanw/clustrast.

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