scholarly journals sgDI-tector: defective interfering viral genome bioinformatics for detection of coronavirus subgenomic RNAs

RNA ◽  
2021 ◽  
pp. rna.078969.121
Author(s):  
Andrea Di Gioacchino ◽  
Rachel Legendre ◽  
Yannis Rahou ◽  
Valérie Najburg ◽  
Pierre Charneau ◽  
...  
Keyword(s):  
Regulatory Sequences ◽  
Accessory Proteins ◽  
Viral Genomes ◽  
Bioinformatic Tools ◽  
Subgenomic Rnas ◽  
Next Generation Sequencing Ngs ◽  
User Friendly ◽  
Ngs Data ◽  
Initial Knowledge ◽  
Generation Sequencing

Coronavirus RNA-dependent RNA polymerases produce subgenomic RNAs (sgRNAs) that encode viral structural and accessory proteins. User-friendly bioinformatic tools to detect and quantify sgRNA production are urgently needed to study the growing number of next-generation sequencing (NGS) data of SARS-CoV-2. We introduced sgDI-tector to identify and quantify sgRNA in SARS-CoV-2 NGS data. sgDI-tector allowed detection of sgRNA without initial knowledge of the transcription-regulatory sequences. We produced NGS data and successfully detected the nested set of sgRNAs with the ranking M>ORF3a>N>ORF6>ORF7a>ORF8>S>E>ORF7b. We also compared the level of sgRNA production with other types of viral RNA products such as defective interfering viral genomes.

scholarly journals sgDI-tector: defective interfering viral genome bioinformatics for detection of coronavirus subgenomic RNAs

2021 ◽  
Author(s):  
Andrea Di Gioacchino ◽  
Rachel Legendre ◽  
Yannis Rahou ◽  
Valerie Najburg ◽  
Pierre Charneau ◽  
...  
Keyword(s):  
Regulatory Sequences ◽  
Accessory Proteins ◽  
Viral Genomes ◽  
Bioinformatic Tools ◽  
Subgenomic Rnas ◽  
Next Generation Sequencing Ngs ◽  
User Friendly ◽  
Ngs Data ◽  
Initial Knowledge ◽  
Generation Sequencing

Coronavirus RNA-dependent RNA polymerases produce subgenomic RNAs (sgRNAs) that encode viral structural and accessory proteins. User-friendly bioinformatic tools to detect and quantify sgRNA production are urgently needed to study the growing number of next-generation sequencing (NGS) data of SARS-CoV-2. We introduced sgDI-tector to identify and quantify sgRNA in SARS-CoV-2 NGS data. sgDI-tector allowed detection of sgRNA without initial knowledge of the transcription-regulatory sequences. We produced NGS data and successfully detected the nested set of sgRNAs with the ranking M>ORF3a>N>ORF6>ORF7a>ORF8>S>E>ORF7b. We also compared the level of sgRNA production with other types of viral RNA products such as defective interfering viral genomes.

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 GenoDup Pipeline: a tool to detect genome duplication using the dS-based method

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e6303 ◽  
Author(s):  
Yafei Mao
Keyword(s):  
Next Generation Sequencing ◽  
Evolutionary Biology ◽  
Whole Genome Duplication ◽  
Genome Duplication ◽  
Genomic Data ◽  
Whole Genome ◽  
Next Generation Sequencing Ngs ◽  
User Friendly ◽  
Ngs Data ◽  
Generation Sequencing

Understanding whole genome duplication (WGD), or polyploidy, is fundamental to investigating the origin and diversification of organisms in evolutionary biology. The wealth of genomic data generated by next generation sequencing (NGS) has resulted in an urgent need for handy and accurate tools to detect WGD. Here, I present a useful and user-friendly pipeline called GenoDup for inferring WGD using the dS-based method. I have successfully applied GenoDup to identify WGD in empirical data from both plants and animals. The GenoDup Pipeline provides a reliable and useful tool to infer WGD from NGS data.

scholarly journals GenoDup Pipeline: a tool to detect genome duplication using the dS-based method

2018 ◽  
Author(s):  
Yafei Mao ◽  
Noriyuki Satoh
Keyword(s):  
Next Generation Sequencing ◽  
Evolutionary Biology ◽  
Whole Genome Duplication ◽  
Genome Duplication ◽  
Genomic Data ◽  
Whole Genome ◽  
Next Generation Sequencing Ngs ◽  
User Friendly ◽  
Ngs Data ◽  
Generation Sequencing

ABSTRACTUnderstanding whole genome duplication (WGD), or polyploidy, is fundamental to investigating the origin and diversification of organisms in evolutionary biology. The wealth of genomic data generated by next generation sequencing (NGS) has resulted in an urgent need for robust and accurate tools to detect WGD. Here, we present a useful and user-friendly pipeline called GenoDup for inferring WGD using the dS-based method. We have successfully applied GenoDup to identify WGD in empirical data from both plants and animals. The GenoDup Pipeline provides a reliable and useful tool to infer WGD from NGS data.

scholarly journals Easymap: a user-friendly software package for rapid mapping by sequencing of point mutations and large insertions

2021 ◽  
Author(s):  
Samuel Daniel Lup ◽  
David Wilson-Sánchez ◽  
Sergio Andreu-Sánchez ◽  
José Luis Micol
Keyword(s):  
Point Mutations ◽  
Rapid Identification ◽  
Rna Seq ◽  
Source Program ◽  
Ethylmethane Sulfonate ◽  
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 in order to identify a causal mutation are available; however, the installation and usage of such programs requires bioinformatic skills, modifying or combining pieces of existent 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 ethylmethane sulfonate (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.

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 Mining and Development of Novel SSR Markers Using Next Generation Sequencing (NGS) Data in Plants

Molecules ◽  
2018 ◽  
Vol 23 (2) ◽  
pp. 399 ◽  
Author(s):  
Sima Taheri ◽  
Thohirah Lee Abdullah ◽  
Mohd Yusop ◽  
Mohamed Hanafi ◽  
Mahbod Sahebi ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Ssr Markers ◽  
Next Generation ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data ◽  
Generation Sequencing

scholarly journals The ICR96 exon CNV validation series: a resource for orthogonal assessment of exon CNV calling in NGS data

2017 ◽  
Vol 2 ◽  
pp. 35 ◽  
Author(s):  
Shazia Mahamdallie ◽  
Elise Ruark ◽  
Shawn Yost ◽  
Emma Ramsay ◽  
Imran Uddin ◽  
...  
Keyword(s):  
Sequencing Data ◽  
Targeted Next Generation Sequencing ◽  
Negative Results ◽  
Targeted Ngs ◽  
Predisposition Genes ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data ◽  
Validation Series ◽  
Generation Sequencing ◽  
Dependent Probe

Detection of deletions and duplications of whole exons (exon CNVs) is a key requirement of genetic testing. Accurate detection of this variant type has proved very challenging in targeted next-generation sequencing (NGS) data, particularly if only a single exon is involved. Many different NGS exon CNV calling methods have been developed over the last five years. Such methods are usually evaluated using simulated and/or in-house data due to a lack of publicly-available datasets with orthogonally generated results. This hinders tool comparisons, transparency and reproducibility. To provide a community resource for assessment of exon CNV calling methods in targeted NGS data, we here present the ICR96 exon CNV validation series. The dataset includes high-quality sequencing data from a targeted NGS assay (the TruSight Cancer Panel) together with Multiplex Ligation-dependent Probe Amplification (MLPA) results for 96 independent samples. 66 samples contain at least one validated exon CNV and 30 samples have validated negative results for exon CNVs in 26 genes. The dataset includes 46 exon CNVs in BRCA1, BRCA2, TP53, MLH1, MSH2, MSH6, PMS2, EPCAM or PTEN, giving excellent representation of the cancer predisposition genes most frequently tested in clinical practice. Moreover, the validated exon CNVs include 25 single exon CNVs, the most difficult type of exon CNV to detect. The FASTQ files for the ICR96 exon CNV validation series can be accessed through the European-Genome phenome Archive (EGA) under the accession number EGAS00001002428.

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