High-Throughput and Accurate Determination of Transgene Copy Number and Zygosity in Transgenic Maize: From DNA Extraction to Data Analysis

It is vital to develop high-throughput methods to determine transgene copy numbers initially and zygosity during subsequent breeding. In this study, the target sequence of the previously reported endogenous reference gene hmg was analyzed using 633 maize inbred lines, and two SNPs were observed. These SNPs significantly increased the PCR efficiency, while the newly developed hmg gene assay (hmg-taq-F2/R2) excluding these SNPs reduced the efficiency into normal ranges. The TaqMan amplification efficiency of bar and hmg with newly developed primers was calculated as 0.993 and 1.000, respectively. The inter-assay coefficient of variation (CV) values for the bar and hmg genes varied from 1.18 to 2.94%. The copy numbers of the transgene bar using new TaqMan assays were identical to those using dPCR. Significantly, the precision of one repetition reached 96.7% of that of three repetitions of single-copy plants analyzed by simple random sampling, and the actual accuracy reached 95.8%, confirmed by T1 and T2 progeny. With the high-throughput DNA extraction and automated data analysis procedures developed in this study, nearly 2700 samples could be analyzed within eight hours by two persons. The combined results suggested that the new hmg gene assay developed here could be a universal maize reference gene system, and the new assay has high throughput and high accuracy for large-scale screening of maize varieties around the world.

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Advancing clinical genomics and precision medicine with GVViZ: FAIR bioinformatics platform for variable gene-disease annotation, visualization, and expression analysis

Human Genomics ◽

10.1186/s40246-021-00336-1 ◽

2021 ◽

Vol 15 (1) ◽

Author(s):

Zeeshan Ahmed ◽

Eduard Gibert Renart ◽

Saman Zeeshan ◽

XinQi Dong

Keyword(s):

Data Analysis ◽

Patient Care ◽

Expression Analysis ◽

High Throughput ◽

Gene Annotation ◽

Next Generation Sequencing Data ◽

Rna Seq ◽

Sequencing Data ◽

Complex Disorders ◽

Transcriptomics Data

Abstract Background Genetic disposition is considered critical for identifying subjects at high risk for disease development. Investigating disease-causing and high and low expressed genes can support finding the root causes of uncertainties in patient care. However, independent and timely high-throughput next-generation sequencing data analysis is still a challenge for non-computational biologists and geneticists. Results In this manuscript, we present a findable, accessible, interactive, and reusable (FAIR) bioinformatics platform, i.e., GVViZ (visualizing genes with disease-causing variants). GVViZ is a user-friendly, cross-platform, and database application for RNA-seq-driven variable and complex gene-disease data annotation and expression analysis with a dynamic heat map visualization. GVViZ has the potential to find patterns across millions of features and extract actionable information, which can support the early detection of complex disorders and the development of new therapies for personalized patient care. The execution of GVViZ is based on a set of simple instructions that users without a computational background can follow to design and perform customized data analysis. It can assimilate patients’ transcriptomics data with the public, proprietary, and our in-house developed gene-disease databases to query, easily explore, and access information on gene annotation and classified disease phenotypes with greater visibility and customization. To test its performance and understand the clinical and scientific impact of GVViZ, we present GVViZ analysis for different chronic diseases and conditions, including Alzheimer’s disease, arthritis, asthma, diabetes mellitus, heart failure, hypertension, obesity, osteoporosis, and multiple cancer disorders. The results are visualized using GVViZ and can be exported as image (PNF/TIFF) and text (CSV) files that include gene names, Ensembl (ENSG) IDs, quantified abundances, expressed transcript lengths, and annotated oncology and non-oncology diseases. Conclusions We emphasize that automated and interactive visualization should be an indispensable component of modern RNA-seq analysis, which is currently not the case. However, experts in clinics and researchers in life sciences can use GVViZ to visualize and interpret the transcriptomics data, making it a powerful tool to study the dynamics of gene expression and regulation. Furthermore, with successful deployment in clinical settings, GVViZ has the potential to enable high-throughput correlations between patient diagnoses based on clinical and transcriptomics data.

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High-throughput single cell data analysis – A tutorial

Analytica Chimica Acta ◽

10.1016/j.aca.2021.338872 ◽

2021 ◽

pp. 338872

Author(s):

Gerjen H. Tinnevelt ◽

Kristiaan Wouters ◽

Geert J. Postma ◽

Rita Folcarelli ◽

Jeroen J. Jansen

Keyword(s):

Data Analysis ◽

Single Cell ◽

High Throughput ◽

Cell Data

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A high-throughput plant DNA extraction method for marker analysis

Plant Molecular Biology Reporter ◽

10.1007/bf02773402 ◽

2003 ◽

Vol 21 (1) ◽

pp. 95-95 ◽

Cited By ~ 26

Author(s):

Angelo Karakousis ◽

Peter Langridge

Keyword(s):

Dna Extraction ◽

High Throughput ◽

Extraction Method ◽

Plant Dna ◽

Dna Extraction Method ◽

Marker Analysis

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Improvements and impacts of GRCh38 human reference on high throughput sequencing data analysis

Genomics ◽

10.1016/j.ygeno.2017.01.005 ◽

2017 ◽

Vol 109 (2) ◽

pp. 83-90 ◽

Cited By ~ 44

Author(s):

Yan Guo ◽

Yulin Dai ◽

Hui Yu ◽

Shilin Zhao ◽

David C. Samuels ◽

...

Keyword(s):

Data Analysis ◽

High Throughput ◽

High Throughput Sequencing ◽

Sequencing Data ◽

High Throughput Sequencing Data ◽

Sequencing Data Analysis

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Method Comparison of DNA Isolation and Quantification for Fish and Seafood Authenticity Determination

SQUALEN Bulletin of Marine and Fisheries Postharvest and Biotechnology ◽

10.15578/squalen.v13i3.370 ◽

2018 ◽

Vol 13 (3) ◽

pp. 115

Author(s):

Dwiyitno Dwiyitno ◽

Stefan Hoffman ◽

Koen Parmentier ◽

Chris Van Keer

Keyword(s):

Polymerase Chain Reaction ◽

Dna Extraction ◽

Dna Isolation ◽

Blue Mussel ◽

Pcr Amplification ◽

Amplification Efficiency ◽

Chain Reaction ◽

Seafood Products ◽

Polymerase Chain ◽

Commercial Kit

Fish and seafood products has been commonly targeted for fraudulent activities. For that reason, authentication of fish and seafood products is important to protect consumers from fraudulent and adulteration practices, as well as to implement traceability regulation. From the viewpoint of food safety, authenticity is beneficial to protect public from serious food poisoning incidents, such as due to ingestion of toxic species. Since DNA based identification depends on the nucleic acid polymerase chain reaction (PCR), the quantity and quality/purity of DNA will contribute significantly to the species authentication. In the present study, different DNA extraction and purification methods (3 classical methods and one commercial kit) were compared to produce the better isolated DNA for PCR amplification. Additionally, different methods for the estimation of DNA concentration and purity which is essential for PCR amplification efficiency were also evaluated. The result showed that classical DNA extraction methods (based on TNES-Urea) yielded a higher amount of DNA (11.30-323.60 ng/g tissue) in comparison to commercial kit/Wizard Promega (5.70-83.45 ng/g tissue). Based on the purity of DNA extract (A260/280), classical DNA extraction method produced relatively similar on DNA quality to the commercial kit (1.79-2.12). Interestingly, all classical methods produced DNA with A260/280 ratio of more than 2.00 on the blue mussel, in contrast with commercial kit. The commercial kit also produced better quality of DNA compared to the classical methods, showing the higher efficiency in PCR amplification. NanoDrop is promising as cheap, robust and safe UV-spectrophotometer method for DNA quantification, as well as the purity evaluation.Keywords: seafood authenticity, DNA isolation, polymerase chain reaction, NanoDrop, Picogreen

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ReactomeFIViz: the Reactome FI Cytoscape app for pathway and network-based data analysis

F1000Research ◽

10.12688/f1000research.4431.1 ◽

2014 ◽

Vol 3 ◽

pp. 146 ◽

Cited By ~ 2

Author(s):

Guanming Wu ◽

Eric Dawson ◽

Adrian Duong ◽

Robin Haw ◽

Lincoln Stein

Keyword(s):

Experimental Data ◽

Data Analysis ◽

Graphical Models ◽

High Throughput ◽

Interaction Network ◽

Large Data ◽

Relevant Information ◽

Data Sets ◽

Data Types ◽

Biological Studies

High-throughput experiments are routinely performed in modern biological studies. However, extracting meaningful results from massive experimental data sets is a challenging task for biologists. Projecting data onto pathway and network contexts is a powerful way to unravel patterns embedded in seemingly scattered large data sets and assist knowledge discovery related to cancer and other complex diseases. We have developed a Cytoscape app called “ReactomeFIViz”, which utilizes a highly reliable gene functional interaction network and human curated pathways from Reactome and other pathway databases. This app provides a suite of features to assist biologists in performing pathway- and network-based data analysis in a biologically intuitive and user-friendly way. Biologists can use this app to uncover network and pathway patterns related to their studies, search for gene signatures from gene expression data sets, reveal pathways significantly enriched by genes in a list, and integrate multiple genomic data types into a pathway context using probabilistic graphical models. We believe our app will give researchers substantial power to analyze intrinsically noisy high-throughput experimental data to find biologically relevant information.

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The Fellowship of the Ring Test: DNAqua-Net WG2 initiative to compare diatom metabarcoding protocols used in routine freshwater biomonitoring for standardisation

ARPHA Conference Abstracts ◽

10.3897/aca.4.e65142 ◽

2021 ◽

Vol 4 ◽

Author(s):

Valentin Vasselon ◽

Éva Ács ◽

Salomé Almeida ◽

Karl Andree ◽

Laure Apothéloz-Perret-Gentil ◽

...

Keyword(s):

Dna Extraction ◽

High Throughput ◽

Aquatic Ecosystems ◽

Quality Index ◽

Ecological Status ◽

Pcr Amplification ◽

Ring Test ◽

Dna Metabarcoding ◽

Ecological Status Assessment ◽

Status Assessment

During the past decade genetic approaches have been developed to monitor biodiversity in aquatic ecosystems. These enable access to taxonomic and genetic information from biological communities using DNA from environmental samples (e.g. water, biofilm, soil) and methods based on high-throughput sequencing technologies, such as DNA metabarcoding. Within the context of the Water Framework Directive (WFD), such approaches could be applied to assess Biological Quality Elements (BQE). These are used as indicators of the ecological status of aquatic ecosystems as part of national monitoring programs of the european network of 110,000 surface water monitoring sites with 79.5% rivers and 11% lake sites (Charles et al. 2020). A high-throughput method has the potential to increase our spatio-temporal monitoring capacity and to accelerate the transfer of information to water managers with the aim to increase protection of aquatic ecosystems. Good progress has been made with developing DNA metabarcoding approaches for benthic diatom assemblages. Technological innovation and protocol optimization have allowed robust taxonomic (species) and genetic (OTU, ESV) information to be obtained from which diatom quality indices can be calculated to infer ecological status to rivers and lakes. Diatom DNA metabarcoding has been successfully applied for biomonitoring at the scale of national river monitoring networks in several countries around the world and can now be considered technically ready for routine application (e.g. Apothéloz-Perret-Gentil et al. 2017, Bailet et al. 2019, Mortágua et al. 2019, Vasselon et al. 2019, Kelly et al. 2020, Pérez-Burillo et al. 2020, Pissaridou et al. 2021). However, protocols and methods used by each laboratory still vary between and within countries, limiting their operational transferability and the ability to compare results. Thus, routine use of DNA metabarcoding for diatom biomonitoring requires standardization of all steps of the metabarcoding procedure, from the sampling to the final ecological status assessment in order to define good practices and standards. Following previous initiatives which resulted in a CEN technical report for biofilm sampling and preservation (CEN 2018), a set of experiments was initiated during the DNAqua-Net WG2 diatom workshop (Cyprus, 2019) to focus on DNA extraction and PCR amplification steps in order to evaluate: i) the transferability and reproducibility of a protocol between different laboratories; ii) the variability introduced by different protocols currently applied by the scientific community. 19 participants from 14 countries performed DNA extraction and PCR amplification in parallel, using i) the same fixed protocol and ii) their own protocol. Experiments were performed by each participant on a set of standardized DNA and biofilm samples (river, lake, mock community). In order to specifically test the variability of DNA extraction and PCR amplification steps, all other steps of the metabarcoding process were fixed and the preparation of the Miseq sequencing was performed by only one laboratory. The variability within and between participants will be evaluated on DNA extracts quantity, taxonomic (genus, species) and genetic richness, community structure comparison and diatom quality index scores (IPS). We will also evaluate the variability introduced by different DNA extraction and PCR amplification protocols on diatom quality index scores and the final ecological status assessment. The results from this collaborative work will not serve to define “one protocol to rule them all”, but will provide valuable information to define guidelines and minimum requirements that should be considered when performing diatom metabarcoding for biomonitoring.

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