scholarly journals DIANA-mAP: Analyzing miRNA from Raw NGS Data to Quantification

Genes ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 46
Author(s):  
Athanasios Alexiou ◽  
Dimitrios Zisis ◽  
Ioannis Kavakiotis ◽  
Marios Miliotis ◽  
Antonis Koussounadis ◽  
...  
Keyword(s):  
Expression Profiles ◽  
Differential Expression Analysis ◽  
Rna Seq ◽  
Rna Quantification ◽  
Non Coding Rna ◽  
Data Production ◽  
Ngs Data Analysis ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data ◽  
Generation Sequencing

microRNAs (miRNAs) are small non-coding RNAs (~22 nts) that are considered central post-transcriptional regulators of gene expression and key components in many pathological conditions. Next-Generation Sequencing (NGS) technologies have led to inexpensive, massive data production, revolutionizing every research aspect in the fields of biology and medicine. Particularly, small RNA-Seq (sRNA-Seq) enables small non-coding RNA quantification on a high-throughput scale, providing a closer look into the expression profiles of these crucial regulators within the cell. Here, we present DIANA-microRNA-Analysis-Pipeline (DIANA-mAP), a fully automated computational pipeline that allows the user to perform miRNA NGS data analysis from raw sRNA-Seq libraries to quantification and Differential Expression Analysis in an easy, scalable, efficient, and intuitive way. Emphasis has been given to data pre-processing, an early, critical step in the analysis for the robustness of the final results and conclusions. Through modularity, parallelizability and customization, DIANA-mAP produces high quality expression results, reports and graphs for downstream data mining and statistical analysis. In an extended evaluation, the tool outperforms similar tools providing pre-processing without any adapter knowledge. Closing, DIANA-mAP is a freely available tool. It is available dockerized with no dependency installations or standalone, accompanied by an installation manual through Github.

scholarly journals Patient Derived Xenografts for Genome-Driven Therapy of Osteosarcoma

Cells ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 416
Author(s):  
Lorena Landuzzi ◽  
Maria Cristina Manara ◽  
Pier-Luigi Lollini ◽  
Katia Scotlandi
Keyword(s):  
Clinical Trials ◽  
Tumor Heterogeneity ◽  
Functional Studies ◽  
Ngs Data Analysis ◽  
The Many ◽  
Orthotopic Xenografts ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data ◽  
Generation Sequencing ◽  
Somatic Copy Number Alterations

Osteosarcoma (OS) is a rare malignant primary tumor of mesenchymal origin affecting bone. It is characterized by a complex genotype, mainly due to the high frequency of chromothripsis, which leads to multiple somatic copy number alterations and structural rearrangements. Any effort to design genome-driven therapies must therefore consider such high inter- and intra-tumor heterogeneity. Therefore, many laboratories and international networks are developing and sharing OS patient-derived xenografts (OS PDX) to broaden the availability of models that reproduce OS complex clinical heterogeneity. OS PDXs, and new cell lines derived from PDXs, faithfully preserve tumor heterogeneity, genetic, and epigenetic features and are thus valuable tools for predicting drug responses. Here, we review recent achievements concerning OS PDXs, summarizing the methods used to obtain ectopic and orthotopic xenografts and to fully characterize these models. The availability of OS PDXs across the many international PDX platforms and their possible use in PDX clinical trials are also described. We recommend the coupling of next-generation sequencing (NGS) data analysis with functional studies in OS PDXs, as well as the setup of OS PDX clinical trials and co-clinical trials, to enhance the predictive power of experimental evidence and to accelerate the clinical translation of effective genome-guided therapies for this aggressive disease.

scholarly journals Discovering Selected Antibodies From Deep-Sequenced Phage-Display Antibody Library Using ATTILA

2020 ◽  
Vol 14 ◽  
pp. 117793222091524 ◽  
Author(s):  
Andréa Queiroz Maranhão ◽  
Heidi Muniz Silva ◽  
Waldeyr Mendes Cordeiro da Silva ◽  
Renato Kaylan Alves França ◽  
Thais Canassa De Leo ◽  
...  
Keyword(s):  
Phage Display ◽  
Fold Change ◽  
Robust Solution ◽  
Performance Accuracy ◽  
Variable Domains ◽  
Ngs Data Analysis ◽  
Complementarity Determining Regions ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data ◽  
Generation Sequencing

Phage display is a powerful technique to select high-affinity antibodies for different purposes, including biopharmaceuticals. Next-generation sequencing (NGS) presented itself as a robust solution, making it possible to assess billions of sequences of the variable domains from selected sublibraries. Handling this process, a central difficulty is to find the selected clones. Here, we present the AutomaTed Tool For Immunoglobulin Analysis (ATTILA), a new tool to analyze and find the enriched variable domains throughout a biopanning experiment. The ATTILA is a workflow that combines publicly available tools and in-house programs and scripts to find the fold-change frequency of deeply sequenced amplicons generated from selected VH and VL domains. We analyzed the same human Fab library NGS data using ATTILA in 5 different experiments, as well as on 2 biopanning experiments regarding performance, accuracy, and output. These analyses proved to be suitable to assess library variability and to list the more enriched variable domains, as ATTILA provides a report with the amino acid sequence of each identified domain, along with its complementarity-determining regions (CDRs), germline classification, and fold change. Finally, the methods employed here demonstrated a suitable manner to combine amplicon generation and NGS data analysis to discover new monoclonal antibodies (mAbs).

scholarly journals SequencEnG: an Interactive Knowledge Base of Sequencing Techniques

2018 ◽  
Author(s):  
Yi Zhang ◽  
Mohith Manjunath ◽  
Yeonsung Kim ◽  
Joerg Heintz ◽  
Jun S. Song
Keyword(s):  
Knowledge Base ◽  
Educational Resource ◽  
Rapid Progress ◽  
Structured Knowledge ◽  
Ngs Data Analysis ◽  
Next Generation Sequencing Ngs ◽  
User Friendly ◽  
Ngs Data ◽  
Generation Sequencing ◽  
Acute Challenge

AbstractNext-generation sequencing (NGS) techniques are revolutionizing biomedical research by providing powerful methods for generating genomic and epigenomic profiles. The rapid progress is posing an acute challenge to students and researchers to stay acquainted with the numerous available methods. We have developed an interactive online educational resource called SequencEnG (acronym for Sequencing Techniques Engine for Genomics) to provide a tree-structured knowledge base of 66 different sequencing techniques and step-by-step NGS data analysis pipelines comparing popular tools. SequencEnG is designed to facilitate barrier-free learning of current NGS techniques and provides a user-friendly interface for searching through experimental and analysis methods. SequencEnG is part of the project KnowEnG (Knowledge Engine for Genomics) and is freely available at http://education.knoweng.org/sequenceng/.

scholarly journals Easymap: A User-Friendly Software Package for Rapid Mapping-by-Sequencing of Point Mutations and Large Insertions

2021 ◽  
Vol 12 ◽  
Author(s):  
Samuel Daniel Lup ◽  
David Wilson-Sánchez ◽  
Sergio Andreu-Sánchez ◽  
José Luis Micol
Keyword(s):  
Point Mutations ◽  
Rapid Identification ◽  
Graphical Interface ◽  
Rna Seq ◽  
Source Program ◽  
Next Generation Sequencing Ngs ◽  
User Friendly ◽  
Ngs Data ◽  
Mapping By Sequencing ◽  
Generation Sequencing

Mapping-by-sequencing strategies combine next-generation sequencing (NGS) with classical linkage analysis, allowing rapid identification of the causal mutations of the phenotypes exhibited by mutants isolated in a genetic screen. Computer programs that analyze NGS data obtained from a mapping population of individuals derived from a mutant of interest to identify a causal mutation are available; however, the installation and usage of such programs requires bioinformatic skills, modifying or combining pieces of existing software, or purchasing licenses. To ease this process, we developed Easymap, an open-source program that simplifies the data analysis workflows from raw NGS reads to candidate mutations. Easymap can perform bulked segregant mapping of point mutations induced by ethyl methanesulfonate (EMS) with DNA-seq or RNA-seq datasets, as well as tagged-sequence mapping for large insertions, such as transposons or T-DNAs. The mapping analyses implemented in Easymap have been validated with experimental and simulated datasets from different plant and animal model species. Easymap was designed to be accessible to all users regardless of their bioinformatics skills by implementing a user-friendly graphical interface, a simple universal installation script, and detailed mapping reports, including informative images and complementary data for assessment of the mapping results. Easymap is available at http://genetics.edu.umh.es/resources/easymap; its Quickstart Installation Guide details the recommended procedure for installation.

scholarly journals Mining of miRNAs using Next Generation Sequencing (NGS) data generated for Okra (Abelmoschus esculentus)

2018 ◽  
Vol 13 (2) ◽  
pp. 137-145
Author(s):  
Rekha Gupta ◽  
M Gayathri ◽  
V Radhika ◽  
M Pichaimuthu ◽  
K V Ravishankar
Keyword(s):  
Gene Expression ◽  
Mirna Family ◽  
Abelmoschus Esculentus ◽  
Stem Loop ◽  
Rna Molecules ◽  
Non Coding Rna ◽  
Precursor Rna ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data ◽  
Generation Sequencing

MicroRNAs (miRNAs) are small, highly conserved non-coding RNA molecules involved in theregulation of gene expression in eukaryotes. Gene expression involves post-transcriptionalgene regulation by miRNAs. miRNAs are formed from precursor RNA molecules that fold intoa stem loop secondary structure. The mature miRNA is one end of the precursor miRNA,defined by the cut from ‘Drosha’ on either the 5’ or 3’ arm. In this study, we have used abioinformatics approach to identify miRNAs in 3,361 contigs obtained from partial genomesequence data of Abelmoschus esculentus (okra) sequenced by NGS technology. Using C-miiand psRNA Target tools, we identified two miRNAs and their target RNAs for which a regulatorymiRNA binding has been verified. Their targets consisted of transcription factors involved ingrowth and development, gene regulation and metabolism. Phylogenetic analysis of the newlyidentified miRNA family has been done to compare their level of conservation with respect tothe other members of the plant kingdom.

Introduction to the analysis of next generation sequencing data and its application to venous thromboembolism

2015 ◽  
Vol 114 (11) ◽  
pp. 920-932 ◽  
Author(s):  
Joost C. M. Meijers ◽  
Saskia Middeldorp ◽  
Marisa L. R. Cunha
Keyword(s):  
Venous Thromboembolism ◽  
Next Generation Sequencing ◽  
Clinical Care ◽  
Next Generation Sequencing Data ◽  
Next Generation ◽  
Sequencing Data ◽  
Ngs Data Analysis ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data ◽  
Generation Sequencing

SummaryDespite knowledge of various inherited risk factors associated with venous thromboembolism (VTE), no definite cause can be found in about 50% of patients. The application of data-driven searches such as GWAS has not been able to identify genetic variants with implications for clinical care, and unexplained heritability remains. In the past years, the development of several so-called next generation sequencing (NGS) platforms is offering the possibility of generating fast, inexpensive and accurate genomic information. However, so far their application to VTE has been very limited. Here we review basic concepts of NGS data analysis and explore the application of NGS technology to VTE. We provide both computational and biological viewpoints to discuss potentials and challenges of NGS-based studies.

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