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

Evolutionary Biology ◽

Whole Genome Duplication ◽

Genome Duplication ◽

Genomic Data ◽

Whole Genome ◽

User Friendly ◽

Ngs Data ◽

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.

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

PeerJ ◽

10.7717/peerj.6303 ◽

2019 ◽

Vol 7 ◽

pp. e6303 ◽

Cited By ~ 3

Author(s):

Yafei Mao

Keyword(s):

Evolutionary Biology ◽

Whole Genome Duplication ◽

Genome Duplication ◽

Genomic Data ◽

Whole Genome ◽

User Friendly ◽

Ngs Data ◽

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.

Whole genome sequencing suggests transmission of Corynebacterium diphtheriae-caused cutaneous diphtheria in two siblings, Germany, 2018

Eurosurveillance ◽

10.2807/1560-7917.es.2019.24.2.1800683 ◽

2019 ◽

Vol 24 (2) ◽

Cited By ~ 3

Author(s):

Anja Berger ◽

Alexandra Dangel ◽

Tilmann Schober ◽

Birgit Schmidbauer ◽

Regina Konrad ◽

...

Keyword(s):

Whole Genome Sequencing ◽

Genome Sequencing ◽

Corynebacterium Diphtheriae ◽

Whole Genome ◽

Next Generation ◽

Insect Bites ◽

Ngs Data ◽

In September 2018, a child who had returned from Somalia to Germany presented with cutaneous diphtheria by toxigenic Corynebacterium diphtheriae biovar mitis. The child’s sibling had superinfected insect bites harbouring also toxigenic C. diphtheriae. Next generation sequencing (NGS) revealed the same strain in both patients suggesting very recent human-to-human transmission. Epidemiological and NGS data suggest that the two cutaneous diphtheria cases constitute the first outbreak by toxigenic C. diphtheriae in Germany since the 1980s.

Detection of SARS-CoV-2 from patient fecal samples by whole genome sequencing

Gut Pathogens ◽

10.1186/s13099-021-00398-5 ◽

2021 ◽

Vol 13 (1) ◽

Author(s):

Andreas Papoutsis ◽

Thomas Borody ◽

Siba Dolai ◽

Jordan Daniels ◽

Skylar Steinberg ◽

...

Keyword(s):

Nasopharyngeal Swab ◽

Whole Genome ◽

Rt Pcr ◽

Whole Genome Analysis ◽

Fecal Samples ◽

Oral Transmission ◽

Study Participants ◽

Abstract Background SARS-CoV-2 has been detected not only in respiratory secretions, but also in stool collections. Here were sought to identify SARS-CoV-2 by enrichment next-generation sequencing (NGS) from fecal samples, and to utilize whole genome analysis to characterize SARS-CoV-2 mutational variations in COVID-19 patients. Results Study participants underwent testing for SARS-CoV-2 from fecal samples by whole genome enrichment NGS (n = 14), and RT-PCR nasopharyngeal swab analysis (n = 12). The concordance of SARS-CoV-2 detection by enrichment NGS from stools with RT-PCR nasopharyngeal analysis was 100%. Unique variants were identified in four patients, with a total of 33 different mutations among those in which SARS-CoV-2 was detected by whole genome enrichment NGS. Conclusion These results highlight the potential viability of SARS-CoV-2 in feces, its ongoing mutational accumulation, and its possible role in fecal–oral transmission. This study also elucidates the advantages of SARS-CoV-2 enrichment NGS, which may be a key methodology to document complete viral eradication. Trial registration ClinicalTrials.gov, NCT04359836, Registered 24 April 2020, https://clinicaltrials.gov/ct2/show/NCT04359836?term=NCT04359836&draw=2&rank=1).

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

Molecules ◽

10.3390/molecules23020399 ◽

2018 ◽

Vol 23 (2) ◽

pp. 399 ◽

Cited By ~ 41

Author(s):

Sima Taheri ◽

Thohirah Lee Abdullah ◽

Mohd Yusop ◽

Mohamed Hanafi ◽

Mahbod Sahebi ◽

...

Keyword(s):

Ssr Markers ◽

Next Generation ◽

Ngs Data ◽

Appendix A: Common File Types Used in Next-Generation Sequencing (NGS) Data Analysis

Next-Generation Sequencing Data Analysis ◽

10.1201/b19532-20 ◽

2016 ◽

pp. 199-202

Keyword(s):

Data Analysis ◽

Next Generation ◽

Ngs Data Analysis ◽

Ngs Data ◽

ViennaNGS: A toolbox for building efficient next- generation sequencing analysis pipelines

F1000Research ◽

10.12688/f1000research.6157.2 ◽

2015 ◽

Vol 4 ◽

pp. 50 ◽

Cited By ~ 7

Author(s):

Michael T. Wolfinger ◽

Jörg Fallmann ◽

Florian Eggenhofer ◽

Fabian Amman

Keyword(s):

Sequence Motif ◽

Software Components ◽

Sequencing Analysis ◽

Next Generation ◽

File Formats ◽

Next Generation Sequencing Analysis ◽

Ngs Data ◽

Recent achievements in next-generation sequencing (NGS) technologies lead to a high demand for reuseable software components to easily compile customized analysis workflows for big genomics data. We present ViennaNGS, an integrated collection of Perl modules focused on building efficient pipelines for NGS data processing. It comes with functionality for extracting and converting features from common NGS file formats, computation and evaluation of read mapping statistics, as well as normalization of RNA abundance. Moreover, ViennaNGS provides software components for identification and characterization of splice junctions from RNA-seq data, parsing and condensing sequence motif data, automated construction of Assembly and Track Hubs for the UCSC genome browser, as well as wrapper routines for a set of commonly used NGS command line tools.