Dataset Information

IMPLANT: a new technique for transgene copy number estimation in plants using a single end-point PCR reaction.

ABSTRACT:

Background

Copy number determination is one of the first steps in the characterization of transgenic plant lines. The classical approach to this, Southern blotting, is time-consuming, expensive and requires massive amounts of high-quality genomic DNA. Other PCR-based techniques are either inaccurate, laborious, or expensive.

Results

Here, we propose a new technique, IMPLANT (Insertion of competitive PCR calibrator for copy number estimation), a competitive PCR-based technique in which the competitor (based on an endogenous gene) is also incorporated in the T-DNA, which then gets integrated in the genome together with the gene of interest. As the number of integrated competitor molecules directly corresponds to the number of transgene copies, the transgene copy number can be determined by a single PCR reaction. We demonstrate that the results of this technique closely correspond with those obtained by segregation analysis in Arabidopsis and digital PCR In rice, indicating that it is a powerful alternative for other techniques for copy number determination.

Conclusions

We show that this technique is not only reliable, but is also faster, easier, and cheaper as compared with other techniques. Accurate results are obtained in both Arabidopsis and rice, but this technique can be easily extended to other organisms and as such can be widely adopted in the field of biotechnology.

SUBMITTER: De Saeger J

PROVIDER: S-EPMC9732982 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature

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Publications

IMPLANT: a new technique for transgene copy number estimation in plants using a single end-point PCR reaction.

De Saeger Jonas J Park Jihae J Thoris Kai K De Bruyn Charlotte C Chung Hoo Sun HS Inzé Dirk D Depuydt Stephen S

Plant methods 20221209 1

<h4>Background</h4>Copy number determination is one of the first steps in the characterization of transgenic plant lines. The classical approach to this, Southern blotting, is time-consuming, expensive and requires massive amounts of high-quality genomic DNA. Other PCR-based techniques are either inaccurate, laborious, or expensive.<h4>Results</h4>Here, we propose a new technique, IMPLANT (Insertion of competitive PCR calibrator for copy number estimation), a competitive PCR-based technique in w ...[more]

PMID: 36494670

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Project description:BackgroundAs compared with traditional transgene copy number detection technologies such as Southern blot analysis, real-time PCR provides a fast, inexpensive and high-throughput alternative. However, the real-time PCR based transgene copy number estimation tends to be ambiguous and subjective stemming from the lack of proper statistical analysis and data quality control to render a reliable estimation of copy number with a prediction value. Despite the recent progresses in statistical analysis of real-time PCR, few publications have integrated these advancements in real-time PCR based transgene copy number determination.ResultsThree experimental designs and four data quality control integrated statistical models are presented. For the first method, external calibration curves are established for the transgene based on serially-diluted templates. The Ct number from a control transgenic event and putative transgenic event are compared to derive the transgene copy number or zygosity estimation. Simple linear regression and two group T-test procedures were combined to model the data from this design. For the second experimental design, standard curves were generated for both an internal reference gene and the transgene, and the copy number of transgene was compared with that of internal reference gene. Multiple regression models and ANOVA models can be employed to analyze the data and perform quality control for this approach. In the third experimental design, transgene copy number is compared with reference gene without a standard curve, but rather, is based directly on fluorescence data. Two different multiple regression models were proposed to analyze the data based on two different approaches of amplification efficiency integration. Our results highlight the importance of proper statistical treatment and quality control integration in real-time PCR-based transgene copy number determination.ConclusionThese statistical methods allow the real-time PCR-based transgene copy number estimation to be more reliable and precise with a proper statistical estimation. Proper confidence intervals are necessary for unambiguous prediction of trangene copy number. The four different statistical methods are compared for their advantages and disadvantages. Moreover, the statistical methods can also be applied for other real-time PCR-based quantification assays including transfection efficiency analysis and pathogen quantification.

Project description:Carbapenemase production is one of the leading mechanisms of carbapenem resistance in Gram-negative bacteria. An increase in carbapenemase gene (blaCarb) copies is an important mechanism of carbapenem resistance. No currently available bioinformatics tools allow for reliable detection and reporting of carbapenemase gene copy numbers. Here, we describe the carbapenemase-encoding gene copy number estimator (CCNE), a ready-to-use bioinformatics tool that was developed to estimate blaCarb copy numbers from whole-genome sequencing data. Its performance on Klebsiella pneumoniae carbapenemase gene (blaKPC) copy number estimation was evaluated by simulation and quantitative PCR (qPCR), and the results were compared with available algorithms. CCNE has two components, CCNE-acc and CCNE-fast. CCNE-acc detects blaCarb copy number in a comprehensive and high-accuracy way, while CCNE-fast rapidly screens blaCarb copy numbers. CCNE-acc achieved the best accuracy (100%) and the lowest root mean squared error (RMSE; 0.07) in simulated noise data sets, compared to the assembly-based method (23.4% accuracy, 1.697 RMSE) and the OrthologsBased method (78.9% accuracy, 0.395 RMSE). In the qPCR validation, a high consistency was observed between the blaKPC copy number determined by qPCR and that determined with CCNE. Reverse transcription-qPCR transcriptional analysis of 40 isolates showed that blaKPC expression was positively correlated with the blaKPC copy numbers detected by CCNE (P < 0.001). An association study of 357 KPC-producing K. pneumoniae isolates and their antimicrobial susceptibility identified a significant association between the estimated blaKPC copy number and MICs of imipenem (P < 0.001) and ceftazidime-avibactam (P < 0.001). Overall, CCNE is a useful genomic tool for the analysis of antimicrobial resistance genes copy number; it is available at https://github.com/biojiang/ccne. IMPORTANCE Globally disseminated carbapenem-resistant Enterobacterales is an urgent threat to public health. The most common carbapenem resistance mechanism is the production of carbapenemases. Carbapenemase-producing isolates often exhibit a wide range of carbapenem MICs. Higher carbapenem MICs have been associated with treatment failure. The increase of carbapenemase gene (blaCarb) copy numbers contributes to increased carbapenem MICs. However, blaCarb gene copy number detection is not routinely conducted during a genomic analysis, in part due to the lack of optimal bioinformatics tools. In this study, we describe a ready-to-use tool we developed and designated the carbapenemase-encoding gene copy number estimator (CCNE) that can be used to estimate the blaCarb copy number directly from whole-genome sequencing data, and we extended the data to support the analysis of all known blaCarb genes and some other antimicrobial resistance genes. Furthermore, CCNE can be used to interrogate the correlations between genotypes and susceptibility phenotypes and to improve our understanding of antimicrobial resistance mechanisms.

Dataset Information

IMPLANT: a new technique for transgene copy number estimation in plants using a single end-point PCR reaction.

Background

Results

Conclusions

Publications

IMPLANT: a new technique for transgene copy number estimation in plants using a single end-point PCR reaction.

Similar Datasets

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