scholarly journals Genopo: a nanopore sequencing analysis toolkit for portable Android devices

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Hiruna Samarakoon ◽  
Sanoj Punchihewa ◽  
Anjana Senanayake ◽  
Jillian M. Hammond ◽  
Igor Stevanovski ◽  
...  
Keyword(s):  
Computational Analysis ◽  
Smartphone Application ◽  
Sequencing Analysis ◽  
Nanopore Sequencing ◽  
Android Application ◽  
Sequencing Data ◽  
Human Coronavirus ◽  
Dna And Rna ◽  
Bioinformatics Tools

Abstract The advent of portable nanopore sequencing devices has enabled DNA and RNA sequencing to be performed in the field or the clinic. However, advances in in situ genomics require parallel development of portable, offline solutions for the computational analysis of sequencing data. Here we introduce Genopo, a mobile toolkit for nanopore sequencing analysis. Genopo compacts popular bioinformatics tools to an Android application, enabling fully portable computation. To demonstrate its utility for in situ genome analysis, we use Genopo to determine the complete genome sequence of the human coronavirus SARS-CoV-2 in nine patient isolates sequenced on a nanopore device, with Genopo executing this workflow in less than 30 min per sample on a range of popular smartphones. We further show how Genopo can be used to profile DNA methylation in a human genome sample, illustrating a flexible, efficient architecture that is suitable to run many popular bioinformatics tools and accommodate small or large genomes. As the first ever smartphone application for nanopore sequencing analysis, Genopo enables the genomics community to harness this cheap, ubiquitous computational resource.

scholarly journals Cas9-Assisted Targeting of CHromosome segments (CATCH) for targeted nanopore sequencing and optical genome mapping

2017 ◽  
Author(s):  
Tslil Gabrieli ◽  
Hila Sharim ◽  
Yael Michaeli ◽  
Yuval Ebenstein
Keyword(s):  
Single Molecule ◽  
Genome Mapping ◽  
Single Point ◽  
Read Length ◽  
Whole Genome ◽  
Sequencing Analysis ◽  
Nanopore Sequencing ◽  
Sequencing Data ◽  
Whole Genome Analysis ◽  
Long Read

ABSTRACTVariations in the genetic code, from single point mutations to large structural or copy number alterations, influence susceptibility, onset, and progression of genetic diseases and tumor transformation. Next-generation sequencing analysis is unable to reliably capture aberrations larger than the typical sequencing read length of several hundred bases. Long-read, single-molecule sequencing methods such as SMRT and nanopore sequencing can address larger variations, but require costly whole genome analysis. Here we describe a method for isolation and enrichment of a large genomic region of interest for targeted analysis based on Cas9 excision of two sites flanking the target region and isolation of the excised DNA segment by pulsed field gel electrophoresis. The isolated target remains intact and is ideally suited for optical genome mapping and long-read sequencing at high coverage. In addition, analysis is performed directly on native genomic DNA that retains genetic and epigenetic composition without amplification bias. This method enables detection of mutations and structural variants as well as detailed analysis by generation of hybrid scaffolds composed of optical maps and sequencing data at a fraction of the cost of whole genome sequencing.

Immunoregulation related gene of CSMD2 and RNA activity as potential predicter of 2-year survival in pancreatic cancer: A DNA and RNA sequencing analysis.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e16212-e16212
Author(s):  
Jiafei Yan ◽  
Si Li ◽  
Wenjing Xi ◽  
Dongsheng Chen ◽  
Mingzhe Xiao
Keyword(s):  
Pancreatic Cancer ◽  
T Cell ◽  
Rna Sequencing ◽  
T Cell Activation ◽  
Cell Activation ◽  
Treatment Options ◽  
Cell Activity ◽  
Sequencing Analysis ◽  
Sequencing Data ◽  
Dna And Rna

e16212 Background: The 5-year survival rate of pancreatic cancer remains as low as 3%-15%. One of the key approaches to enrich current treatment options or improve effectiveness is new biomarker probing. We conducted DNA and RNA sequencing analysis to reveal potential biomarkers related to overall survival. Methods: Whole-exome sequencing, RNA sequencing and clinical data for 209 patients with pancreatic cancer were downloaded from TCGA. Clinical factors and mutational landscape (insertion/ deletion/ single nucleotide variant) were compared between group of OS2+ (OS longer than 2 years) and OS2- (OS longer than 2 years) with T test and Chi-square Test. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted with RNA sequencing data to clarify the functional differences between the two groups. Results: The rates of OS2+ for patients in stage of I/II/III/IV was 43% (9/21), 17.8% (27/152), 0% (0/4), 0% (0/5), respectively. 152 patients in stage II were included for further analysis. No difference of sex and age were found between group of OS2+ and OS2-. Tumor mutation burden was comparable between the two groups. Mutation landscape showed the two groups had the accordance of 50% in top 10 genes. Mutations of CSMD2(18.5% vs. 5.0% , P = 0.026), CMYA5(14.8% vs, 2.5% , P = 0.019) and KCNA6(14.8% vs, 3.3%, P = 0.034) were more frequent in OS2+ group. CSMD2 is thought to be involved in the control of complement cascade of the immune system, and its low expression was significantly associated with differentiation, lymphatic invasion, and tumor size in colorectal cancer. CMYA5 was predicted as novel oncogene in breast cancer with the tool of Moonlight, it may also participate tumor activity in pancreatic cancer. The role of KCNA6 in cancer cell activity is barely known yet. Evaluation of differentially expressed genes between the two groups detected difference in leukocyte differentiation and T cell activation (GO analysis) and MAPK signal pathway (KEGG panalysis), these immunoregulation and MAPK pathways may play critical roles in tumor development and progression and affect the prognosis of pancreatic cancer. Conclusions: Pancreatic cancer with 2-year survival presented significant different DNA and RNA alterations, in which CSMD2 and pathway of leukocyte differentiation and T cell activation are closely associated with immunoregulation. These might provide guidance for prognose management and development of new therapeutic targets. Further mechanistic insights and prospective validation studies are warranted.

Computational Analysis of DNA and RNA Sequencing Data Obtained from Liquid Biopsies

2019 ◽  
pp. 347-368 ◽  
Author(s):  
Francesco Marass ◽  
Francesc Castro-Giner ◽  
Barbara Maria Szczerba ◽  
Katharina Jahn ◽  
Jack Kuipers ◽  
...  
Keyword(s):  
Rna Sequencing ◽  
Computational Analysis ◽  
Sequencing Data ◽  
Liquid Biopsies ◽  
Dna And Rna

High-resolution nucleic acid sequence mapping via in situ hybridization at the Electron Microscope level

1995 ◽  
Vol 53 ◽  
pp. 752-753
Author(s):  
B.A. Hamkalo ◽  
S. Narayanswami ◽  
A.P. Kausch
Keyword(s):  
Nucleic Acid ◽  
Interphase Nucleus ◽  
Genome Mapping ◽  
Precise Location ◽  
Electron Microscope Level ◽  
Rna Sequences ◽  
Fundamental Interest ◽  
Whole Cells ◽  
Dna And Rna

The availability of nonradioactive methods to label nucleic acids an the resultant rapid and greater sensitivity of detection has catapulted the technique of in situ hybridization to become the method of choice to locate of specific DNA and RNA sequences on chromosomes and in whole cells in cytological preparations in many areas of biology. It is being applied to problems of fundamental interest to basic cell and molecular biologists such as the organization of the interphase nucleus in the context of putative functional domains; it is making major contributions to genome mapping efforts; and it is being applied to the analysis of clinical specimens. Although fluorescence detection of nucleic acid hybrids is routinely used, certain questions require greater resolution. For example, very closely linked sequences may not be separable using fluorescence; the precise location of sequences with respect to chromosome structures may be below the resolution of light microscopy(LM); and the relative positions of sequences on very small chromosomes may not be feasible.

scholarly journals In situ differentiation of iridophore crystallotypes underlies zebrafish stripe patterning

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Dvir Gur ◽  
Emily J. Bain ◽  
Kory R. Johnson ◽  
Andy J. Aman ◽  
H. Amalia Pasoili ◽  
...  
Keyword(s):  
Skin Color ◽  
Cell Types ◽  
Color Pattern ◽  
Single Type ◽  
Sequencing Analysis ◽  
X Ray Diffraction ◽  
X Ray ◽  
Cryogenic Scanning Electron Microscopy ◽  
Different Cell Types

AbstractSkin color patterns are ubiquitous in nature, impact social behavior, predator avoidance, and protection from ultraviolet irradiation. A leading model system for vertebrate skin patterning is the zebrafish; its alternating blue stripes and yellow interstripes depend on light-reflecting cells called iridophores. It was suggested that the zebrafish’s color pattern arises from a single type of iridophore migrating differentially to stripes and interstripes. However, here we find that iridophores do not migrate between stripes and interstripes but instead differentiate and proliferate in-place, based on their micro-environment. RNA-sequencing analysis further reveals that stripe and interstripe iridophores have different transcriptomic states, while cryogenic-scanning-electron-microscopy and micro-X-ray diffraction identify different crystal-arrays architectures, indicating that stripe and interstripe iridophores are different cell types. Based on these results, we present an alternative model of skin patterning in zebrafish in which distinct iridophore crystallotypes containing specialized, physiologically responsive, organelles arise in stripe and interstripe by in-situ differentiation.

scholarly journals BiSulfite Bolt: A bisulfite sequencing analysis platform

GigaScience ◽  
2021 ◽  
Vol 10 (5) ◽  
Author(s):  
Colin Farrell ◽  
Michael Thompson ◽  
Anela Tosevska ◽  
Adewale Oyetunde ◽  
Matteo Pellegrini
Keyword(s):  
Data Aggregation ◽  
Bisulfite Sequencing ◽  
Low Complexity ◽  
Sequencing Analysis ◽  
Command Line ◽  
Sequencing Data ◽  
Bisulfite Sequencing Data ◽  
Analysis Platform ◽  
Python Package ◽  
Bisulfite Sequencing Analysis

Abstract Background Bisulfite sequencing is commonly used to measure DNA methylation. Processing bisulfite sequencing data is often challenging owing to the computational demands of mapping a low-complexity, asymmetrical library and the lack of a unified processing toolset to produce an analysis-ready methylation matrix from read alignments. To address these shortcomings, we have developed BiSulfite Bolt (BSBolt), a fast and scalable bisulfite sequencing analysis platform. BSBolt performs a pre-alignment sequencing read assessment step to improve efficiency when handling asymmetrical bisulfite sequencing libraries. Findings We evaluated BSBolt against simulated and real bisulfite sequencing libraries. We found that BSBolt provides accurate and fast bisulfite sequencing alignments and methylation calls. We also compared BSBolt to several existing bisulfite alignment tools and found BSBolt outperforms Bismark, BSSeeker2, BISCUIT, and BWA-Meth based on alignment accuracy and methylation calling accuracy. Conclusion BSBolt offers streamlined processing of bisulfite sequencing data through an integrated toolset that offers support for simulation, alignment, methylation calling, and data aggregation. BSBolt is implemented as a Python package and command line utility for flexibility when building informatics pipelines. BSBolt is available at https://github.com/NuttyLogic/BSBolt under an MIT license.

scholarly journals CircAgtpbp1 Acts as a Molecular Sponge of miR-543-5p to Regulate the Secretion of GH in Rat Pituitary Cells

Animals ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 558
Author(s):  
ZeWen Yu ◽  
WenZhi Ren ◽  
Tian Wang ◽  
WeiDi Zhang ◽  
ChangJiang Wang ◽  
...  
Keyword(s):  
Pituitary Gland ◽  
Inhibitory Effect ◽  
Pituitary Cells ◽  
Sequencing Analysis ◽  
Hormone Regulation ◽  
Gh Secretion ◽  
Qrt Pcr ◽  
Rat Pituitary ◽  
Rat Pituitary Cells

CircRNAs have been identified to be expressed differently and stably in numerous species and tissues, but their functions in growth hormone (GH) secretion are still largely unknown. In summary, we have revealed a circRNA-miRNA-mRNA network that may play a biological role in the rat pituitary gland. First, we verified the chromosome location information of circAgtpbp1 according to sequencing analysis. The circAgtpbp1 characteristics were authenticated through PCR, qRT–PCR, treating with RNase and fluorescent in situ hybridization (FISH). Second, we detected the expression pattern of circAgtpbp1 in the rat anterior pituitary by qRT–PCR. We also designed circAgtpbp1 siRNA and constructed overexpression plasmid to evaluate the effect of circAgtpbp1 function on GH secretion by qRT–PCR, ELISA and Western blot. CircAgtpbp1 is a stable, truly circular molecule. We found that circAgtpbp1 interacted with miR-543-5p and can regulate GH secretion in pituitary cells through a circAgtpbp1-miR-543-5p-GH axis. Overall, the evidence generated by our study suggests that circAgtpbp1 can act as a sponge of miR-543-5p to reduce the inhibitory effect of miR-543-5p on Gh1 and further promote GH secretion. These findings expand our existing knowledge on the mechanisms of hormone regulation in the pituitary gland.

scholarly journals Sequoia: an interactive visual analytics platform for interpretation and feature extraction from nanopore sequencing datasets

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Ratanond Koonchanok ◽  
Swapna Vidhur Daulatabad ◽  
Quoseena Mir ◽  
Khairi Reda ◽  
Sarath Chandra Janga
Keyword(s):  
Single Molecule ◽  
Visual Analytics ◽  
Visual Analysis ◽  
Direct Sequencing ◽  
Visual Exploration ◽  
Nanopore Sequencing ◽  
Sequencing Data ◽  
Rna Sequences ◽  
Sequencing Technologies ◽  
Signal Features

Abstract Background Direct-sequencing technologies, such as Oxford Nanopore’s, are delivering long RNA reads with great efficacy and convenience. These technologies afford an ability to detect post-transcriptional modifications at a single-molecule resolution, promising new insights into the functional roles of RNA. However, realizing this potential requires new tools to analyze and explore this type of data. Result Here, we present Sequoia, a visual analytics tool that allows users to interactively explore nanopore sequences. Sequoia combines a Python-based backend with a multi-view visualization interface, enabling users to import raw nanopore sequencing data in a Fast5 format, cluster sequences based on electric-current similarities, and drill-down onto signals to identify properties of interest. We demonstrate the application of Sequoia by generating and analyzing ~ 500k reads from direct RNA sequencing data of human HeLa cell line. We focus on comparing signal features from m6A and m5C RNA modifications as the first step towards building automated classifiers. We show how, through iterative visual exploration and tuning of dimensionality reduction parameters, we can separate modified RNA sequences from their unmodified counterparts. We also document new, qualitative signal signatures that characterize these modifications from otherwise normal RNA bases, which we were able to discover from the visualization. Conclusions Sequoia’s interactive features complement existing computational approaches in nanopore-based RNA workflows. The insights gleaned through visual analysis should help users in developing rationales, hypotheses, and insights into the dynamic nature of RNA. Sequoia is available at https://github.com/dnonatar/Sequoia.

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