scholarly journals Auto-qPCR: A Python based web app for automated and reproducible analysis of qPCR data

2021 ◽  
Author(s):  
Gilles Maussion ◽  
Rhalena A. Thomas ◽  
Iveta Demirova ◽  
Gracia Gu ◽  
Eddie Cai ◽  
...  
Keyword(s):  
Gene Expression ◽  
Molecular Biology ◽  
Data Processing ◽  
Reference Sample ◽  
Basic Research ◽  
Relative Quantification ◽  
Qpcr Data ◽  
Dna And Rna ◽  
Duplication Events ◽  
Programming Knowledge

AbstractQuantifying changes in DNA and RNA levels is an essential component of any molecular biology toolkit. Quantitative real time PCR (qPCR) techniques, in both clinical and basic research labs, have evolved to become both routine and standardized. However, the analysis of qPCR data includes many steps that are time consuming and cumbersome, which can lead to mistakes and misinterpretation of data. To address this bottleneck, we have developed an open source software, written in Python, to automate the processing of csv output files from any qPCR machine, using standard calculations that are usually performed manually. Auto-qPCR is a tool that saves time when computing this type of data, helping to ensure standardization of qPCR experiment analyses. Unlike other software packages that process qPCR data, our web-based app (http://auto-q-pcr.com/) is easy to use and does not require programming knowledge or software installation. Additionally, we provide examples of four different data processing modes within one program: (1) cDNA quantification to identify genomic deletion or duplication events, (2) assessment of gene expression levels using an absolute model, (3) relative quantification, and (4) relative quantification with a reference sample. Auto-qPCR also includes options for statistical analysis of the data. Using this software, we performed analysis of differential gene expression following an initial data processing and provide graphs of the findings prepared through the Auto-qPCR program. Thus, our open access Auto-qPCR software saves the time of manual data analysis and provides a more systematic workflow, minimizing the risk of errors when done manually. Our program constitutes a new tool that can be incorporated into bioinformatic and molecular biology pipelines in clinical and research labs.

scholarly journals Auto-qPCR; a python-based web app for automated and reproducible analysis of qPCR data

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Gilles Maussion ◽  
Rhalena A. Thomas ◽  
Iveta Demirova ◽  
Gracia Gu ◽  
Eddie Cai ◽  
...  
Keyword(s):  
Data Analysis ◽  
Molecular Biology ◽  
Reference Sample ◽  
Qpcr Data ◽  
Dna And Rna ◽  
Processing Modes ◽  
Duplication Events ◽  
Automate Processing ◽  
Reproducible Analysis ◽  
Programming Knowledge

AbstractQuantifying changes in DNA and RNA levels is essential in numerous molecular biology protocols. Quantitative real time PCR (qPCR) techniques have evolved to become commonplace, however, data analysis includes many time-consuming and cumbersome steps, which can lead to mistakes and misinterpretation of data. To address these bottlenecks, we have developed an open-source Python software to automate processing of result spreadsheets from qPCR machines, employing calculations usually performed manually. Auto-qPCR is a tool that saves time when computing qPCR data, helping to ensure reproducibility of qPCR experiment analyses. Our web-based app (https://auto-q-pcr.com/) is easy to use and does not require programming knowledge or software installation. Using Auto-qPCR, we provide examples of data treatment, display and statistical analyses for four different data processing modes within one program: (1) DNA quantification to identify genomic deletion or duplication events; (2) assessment of gene expression levels using an absolute model, and relative quantification (3) with or (4) without a reference sample. Our open access Auto-qPCR software saves the time of manual data analysis and provides a more systematic workflow, minimizing the risk of errors. Our program constitutes a new tool that can be incorporated into bioinformatic and molecular biology pipelines in clinical and research labs.

Molecular Biology and Psychiatry: New Methodologies and Techniques

CNS Spectrums ◽  
1997 ◽  
Vol 2 (9) ◽  
pp. 35-41
Author(s):  
Silvia Marracci ◽  
Donatella Marazziti ◽  
Michela Ori ◽  
Irma Nardi
Keyword(s):  
Gene Expression ◽  
Central Nervous System ◽  
Molecular Biology ◽  
Basic Research ◽  
Biological Psychiatry ◽  
General Information ◽  
General Knowledge ◽  
Expression Studies ◽  
New Methodologies ◽  
Gene Expression Studies

AbstractMolecular biology techniques are used widely in the study of central nervous system structures and functions. The possibilities offered by such methodologies are attracting an increasing number of researchers for their versatility and for their promise to permit the investigation of different proteins, step by step, from gene transcription to posttranscriptional processes. Of particular interest is the study of the enzymes responsible for the synthesis and catabolism of neurotransmitters, as well as neuroreceptors.Today, a general knowledge of such methods and of how they can be used in CNS studies is fundamental for psychiatrists, even if not directly involved in basic research, since it can be easily predicted that the next century will be characterized by an increasing application of these approaches to biological psychiatry. In this article, we describe gene expression methods and the aim of gene expression studies. We also present some general information on the various steps and techniques used for different purposes in biological psychiatry.

scholarly journals Machines on Genes: Enzymes that Make, Break and Move DNA and RNA

2010 ◽  
Vol 38 (2) ◽  
pp. 381-383 ◽  
Author(s):  
W. Marshall Stark ◽  
Ben F. Luisi ◽  
Richard P. Bowater
Keyword(s):  
Gene Expression ◽  
Molecular Biology ◽  
Nucleic Acids ◽  
Present Article ◽  
Genetic Information ◽  
Clear View ◽  
Dna And Rna ◽  
Repair Enzymes ◽  
University Of Cambridge ◽  
Enzyme Substrates

As the vital information repositories of the cell, the nucleic acids DNA and RNA pose many challenges as enzyme substrates. To produce, maintain and repair DNA and RNA, and to extract the genetic information that they encode, a battery of remarkable enzymes has evolved, which includes translocases, polymerases/replicases, helicases, nucleases, topoisomerases, transposases, recombinases, repair enzymes and ribosomes. An understanding of how these enzymes function is essential if we are to have a clear view of the molecular biology of the cell and aspire to manipulate genomes and gene expression to our advantage. To bring together scientists working in this fast-developing field, the Biochemical Society held a Focused Meeting, ‘Machines on Genes: Enzymes that Make, Break and Move DNA and RNA’, at Robinson College, University of Cambridge, U.K., in August 2009. The present article summarizes the research presented at this meeting and the reviews associated with the talks which are published in this issue of Biochemical Society Transactions.

scholarly journals Ectopic targeting of CG DNA methylation in Arabidopsis with the bacterial SssI methyltransferase

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Wanlu Liu ◽  
Javier Gallego-Bartolomé ◽  
Yuxing Zhou ◽  
Zhenhui Zhong ◽  
Ming Wang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Zinc Finger ◽  
Zinc Finger Protein ◽  
Basic Research ◽  
Crop Plant ◽  
Open Chromatin ◽  
Histone Marks ◽  
It Impacts ◽  
Finger Protein

AbstractThe ability to target epigenetic marks like DNA methylation to specific loci is important in both basic research and in crop plant engineering. However, heritability of targeted DNA methylation, how it impacts gene expression, and which epigenetic features are required for proper establishment are mostly unknown. Here, we show that targeting the CG-specific methyltransferase M.SssI with an artificial zinc finger protein can establish heritable CG methylation and silencing of a targeted locus in Arabidopsis. In addition, we observe highly heritable widespread ectopic CG methylation mainly over euchromatic regions. This hypermethylation shows little effect on transcription while it triggers a mild but significant reduction in the accumulation of H2A.Z and H3K27me3. Moreover, ectopic methylation occurs preferentially at less open chromatin that lacks positive histone marks. These results outline general principles of the heritability and interaction of CG methylation with other epigenomic features that should help guide future efforts to engineer epigenomes.

scholarly journals Recent Advances in the Development of Exogenous dsRNA for the Induction of RNA Interference in Cancer Therapy

Molecules ◽  
2021 ◽  
Vol 26 (3) ◽  
pp. 701
Author(s):  
Tatiana S. Golubeva ◽  
Viktoria A. Cherenko ◽  
Konstantin E. Orishchenko
Keyword(s):  
Gene Expression ◽  
Rna Interference ◽  
Molecular Biology ◽  
Gene Silencing ◽  
Regulation Of Gene Expression ◽  
Research Area ◽  
Disease Treatment ◽  
Practical Applications ◽  
Agricultural Plants ◽  
Insect Reproduction

Selective regulation of gene expression by means of RNA interference has revolutionized molecular biology. This approach is not only used in fundamental studies on the roles of particular genes in the functioning of various organisms, but also possesses practical applications. A variety of methods are being developed based on gene silencing using dsRNA—for protecting agricultural plants from various pathogens, controlling insect reproduction, and therapeutic techniques related to the oncological disease treatment. One of the main problems in this research area is the successful delivery of exogenous dsRNA into cells, as this can be greatly affected by the localization or origin of tumor. This overview is dedicated to describing the latest advances in the development of various transport agents for the delivery of dsRNA fragments for gene silencing, with an emphasis on cancer treatment.

Basic research in biochemistry and molecular biology in China: A bibliometric analysis

2005 ◽  
Vol 62 (2) ◽  
pp. 249-259 ◽  
Author(s):  
Tianwei He ◽  
Jinglin Zhang ◽  
Lirong Teng
Keyword(s):  
Molecular Biology ◽  
Bibliometric Analysis ◽  
Basic Research

scholarly journals Review of Current Methodological Approaches for Characterizing MicroRNAs in Plants

2009 ◽  
Vol 2009 ◽  
pp. 1-11 ◽  
Author(s):  
Turgay Unver ◽  
Deana M. Namuth-Covert ◽  
Hikmet Budak
Keyword(s):  
Gene Expression ◽  
Molecular Biology ◽  
Reverse Genetics ◽  
Methodological Approach ◽  
Forward Genetics ◽  
Methodological Approaches

Advances in molecular biology have led to some surprising discoveries. One of these includes the complexities of RNA and its role in gene expression. One particular class of RNA called microRNA (miRNA) is the focus of this paper. We will first briefly look at some of the characteristics and biogenesis of miRNA in plant systems. The remainder of the paper will go into details of three different approaches used to identify and study miRNA. These include two reverse genetics approaches: computation (bioinformatics) and experimental, and one rare forward genetics approach. We also will summarize how to measure and quantify miRNAs, and how to detect their possible targets in plants. Strengths and weaknesses of each methodological approach are discussed.

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