scholarly journals TnClone: high-throughput clonal analysis using Tn5-mediated library construction and de novo assembly

2018 ◽  
Author(s):  
Byungjin Hwang ◽  
Sunghoon Heo ◽  
Namjin Cho ◽  
Duhee Bang

ABSTRACTA typical molecular cloning procedure requires Sanger sequencing for validation, which becomes cost-prohibitive and labour-intensive for large-scale clonal analysis of genotype-phenotype studies. Here we present a Tn5-mediated clonal analysis platform TnClone, which uses next-generation sequencing (NGS) to rapidly and cost-effectively analyze a large number of clones. We also developed a user-friendly graphical user interface and have provided general guidelines for conducting validation experiments. Using TnClone, we achieved more than 20-fold cost reduction compared with the cost incurred using conventional Sanger sequencing and detected low-frequency mutant clones (~10%) in mixed samples. We tested our programme and achieved 99.4% sensitivity. Our platform provides rapid turnaround with minimal hands-on time for secondary evaluation as NGS technology continues to evolve.

2018 ◽  
Author(s):  
Berline Fopa Fomeju ◽  
Dominique Brunel ◽  
Aurélie Bérard ◽  
Jean-Baptiste Rivoal ◽  
Philippe Gallois ◽  
...  

AbstractNext-Generation Sequencing (NGS) technologies, by reducing the cost and increasing the throughput of sequencing, have opened doors of research efforts to generate genomic data to a range of previously poorly studied species. In this study, we proposed a method for the rapid development of a large scale molecular resources for orphan species. We studied as an example Lavandula angustifolia, a perennial sub-shrub plant native from the Mediterranean region and whose essential oil have numerous applications in cosmetics, pharmaceuticals, and alternative medicines.We first built a ‘Maillette’ reference Unigene, compound of coding sequences, thanks to de novo RNA-seq assembly. Then, we reconstructed the complete genes sequences (with exons and introns) using a transcriptome-guided DNA-seq assembly approach in order to maximize the possibilities of finding polymorphism between genetically close individuals. Finally, we used these resources for SNP mining within a collection of 16 lavender clones and tested the SNP within the scope of a phylogeny analysis. We obtained a cleaned reference of 8, 030 functionally annotated ‘genes’ (in silico annotation). We found up to 400K polymorphic sites, depending on the genotype analyzed, and observed a high SNP frequency (mean of 1 SNP per 90 bp) and a high level of heterozygosity (more than 60% of heterozygous SNP per genotype). We found similar genetic distances between pairs of clones, related to the out-crossing nature of the species, the restricted area of cultivation and the clonal propagation of the varieties.The method propose is transferable to other orphan species, requires little bioinformatics resources and can be realized within a year. This is the first reported large-scale SNP development on Lavandula angustifolia. All this data provides a rich pool of molecular resource to explore and exploit biodiversity in breeding programs.


2018 ◽  
Author(s):  
Leandro Gabriel Roser ◽  
Fernán Agüero ◽  
Daniel Oscar Sánchez

AbstractBackgroundExploration and processing of FASTQ files are the first steps in state-of-the-art data analysis workflows of Next Generation Sequencing (NGS) platforms. The large amount of data generated by these technologies has put a challenge in terms of rapid analysis and visualization of sequencing information. Recent integration of the R data analysis platform with web visual frameworks has stimulated the development of user-friendly, powerful, and dynamic NGS data analysis applications.ResultsThis paper presents FastqCleaner, a Bioconductor visual application for both quality-control (QC) and pre-processing of FASTQ files. The interface shows diagnostic information for the input and output data and allows to select a series of filtering and trimming operations in an interactive framework. FastqCleaner combines the technology of Bioconductor for NGS data analysis with the data visualization advantages of a web environment.ConclusionsFastqCleaner is an user-friendly, offline-capable tool that enables access to advanced Bioconductor infrastructure. The novel concept of a Bioconductor interactive application that can be used without the need for programming skills, makes FastqCleaner a valuable resource for NGS data analysis.


2017 ◽  
Vol 88 (6) ◽  
pp. 408-417 ◽  
Author(s):  
Greta Grosse ◽  
Alina Hilger ◽  
Michael Ludwig ◽  
Heiko Reutter ◽  
Franziska Lorenzen ◽  
...  

Background/Aims: To elucidate the genetic causes of severe primary insulin-like growth factor-I deficiency (SPIGFD) by systematic, targeted, next-generation sequencing (NGS)-based resequencing of growth-related genes. Methods: Clinical phenotyping followed by NGS in 17 families including 6 affected sib pairs. Results: We identified disease-causing, heterozygous, de novo variants in HRAS (p.Gly13Cys) and FAM111A (p.Arg569His) in 2 male patients with syndromic SPIGFD. A previously described homozygous GHR nonsense variant was detected in 2 siblings of a consanguineous family (p.Glu198*). Furthermore, we identified an inherited novel variant in the IGF2 gene (p.Arg156Cys) of a maternally imprinted gene in a less severely affected father and his affected daughter. We detected 2 other novel missense variants in SH2B1 and SOCS2, both were inherited from an unaffected parent. Conclusions: Screening of growth-related genes using NGS-based, large-scale, targeted resequencing identified disease-causing variants in HRAS, FAM111A, and GHR. Considering the increased risk of subjects with HRAS mutations for neoplasms, close clinical monitoring and a thorough discussion of the risk/benefit ratio of the treatment with recombinant IGF-I is mandatory. Segregation analysis proved to be critical in the interpretation of potential SPIGFD-associated gene variations.


2018 ◽  
Author(s):  
Ronit Dalmat ◽  
Negar Makhsous ◽  
Gregory Pepper ◽  
Amalia Magaret ◽  
Keith R. Jerome ◽  
...  

AbstractHIV drug resistance genotyping is a critical tool in the clinical management of HIV infections. Although resistance genotyping has traditionally been conducted using Sanger sequencing, next-generation sequencing (NGS) is emerging as a powerful tool due to its ability to detect lower frequency alleles. However, the value added from NGS approaches to antiviral resistance testing remains to be demonstrated. We compared the variant detection capacity of NGS versus Sanger sequencing methods for resistance genotyping of 144 drug resistance tests (105 protease-reverse transcriptase tests and 39 integrase tests) submitted to our clinical virology laboratory over a four-month period in 2016 for Sanger-based HIV drug resistance testing. NGS detected all true high frequency drug resistance mutations (>20% frequency) found by Sanger sequencing, with greater accuracy in one instance of a Sanger-detected false positive. Freely available online NGS variant callers Hydra and PASeq were superior to Sanger methods for interpretations of allele linkage and automated variant calling. NGS additionally detected low frequency mutations (1-20% frequency) associated with higher levels of drug resistance in 30/105 (29%) of protease-reverse transcriptase tests and 4/39 (10%) of integrase tests. Clinical follow-up of 69 individuals for a median of 674 days found no difference in rates of virological failure between individuals with and without low frequency mutations, although rates of virological failure were higher for individuals with drug-relevant low frequency mutations. However, all 27 individuals who experienced virological failure reported poor adherence to their drug regimen during preceding follow-up time, and all 19 who subsequently improved their adherence achieved viral suppression at later time points consistent with a lack of clinical resistance. In conclusion, in a population with low antiviral resistance emergence, NGS methods detected numerous instances of minor alleles that did not result in subsequent bona fide virological failure due to antiviral resistance.ImportanceGenotypic antiviral resistance testing for HIV is an essential component of the clinical microbiology and virology laboratory. Next-generation sequencing (NGS) has emerged as a powerful tool for the detection of low frequency sequence variants (allele frequencies <20%). Whether detecting these low frequency mutations in HIV contributes to improved patient health, however, remains unclear. We compared NGS to conventional Sanger sequencing for detecting resistance mutations for 144 HIV drug resistance tests submitted to our clinical virology laboratory and detected low frequency mutations in 24% of tests. Over approximately two years of follow-up for 69 patients for which we had access to electronic health records, no patients had virological failure due to antiviral resistance. Instead, virological failure was entirely explained by medication non-adherence. While larger studies are required, we suggest that detection of low frequency variants by NGS presents limited marginal clinical utility when compared to standard of care.


Blood ◽  
2014 ◽  
Vol 124 (21) ◽  
pp. 3266-3266
Author(s):  
Cécile Bally ◽  
Aline Renneville ◽  
Lionel Adès ◽  
Claude Preudhomme ◽  
Hugues de Thé ◽  
...  

Abstract Background TP53 mutations inactivating p53 protein, often associated with loss of the remaining TP53 allele through 17p deletion, are major prognostic factors in many hematological malignancies, including CLL, myeloma, AML and MDS. In AML and MDS, they are usually associated with complex karyotype (including del 17p) and very poor prognosis (Blood 1991, 78(7):1652-7 , Bejar, NEJM 2011), including after allogeneic SCT (Middeke JM, Blood 2014) but they are also seen in lower risk MDS with isolated del 5q, where they confer resistance to Lenalidomide (Jadersten, JCO 2011). The advent of Next Generation Sequencing (NGS) techniques has improved the detection of such mutations, by allowing the identification of small mutated clones. Other detection methods may prove interesting, especially functional methods like FASAY ( Functional Assay of Separated Allele in Yeast) , an easy and sensitive method that detects TP53 mutations by assessing the p53 function as transcription factor (Flaman et al, PNAS 1995). We compared the detection of TP53 mutations in MDS and AML by FASAY and NGS approaches. Methods The 84 patients analyzed included 10 AML, 10 higher risk MDS, and 64 lower risk MDS with del 5q. RNA and DNA were extracted from marrow mononuclear cells. TP53 mutations were detected on RNA by FASAY where, after amplification of the TP53 mRNA, the PCR product is co transfected with an open gap repair plasmid leading, by homologous recombination, to p53 protein expression in the yeast. The yeast strain used is dependent on p53 functionality for growth and color and detection of more than 10% of small red yeast colonies defines a non-functional FASAY result. All non-functional FASAY were confirmed by the split versions of the test and TP53 defects were characterized by Sanger sequencing. The detection limit is around 10% in our hands (Manie E, Cancer Res 2009). In parallel, TP53 mutations were detected on DNA by NGS using the IRON II plate design and pyrosequencing on a GS Junior System (Roche). (Kohlmann, Leukemia 2011).FASAY (+Sanger sequencing) and NGS were performed in two different labs. Results By FASAY, 47 patients (56%) had a functional p53 and 37 cases (44%) a non-functional p53 and a mutation was confirmed by Sanger in all non functional cases. By NGS analysis, no TP53 mutation was found in 47 cases (56%) and a mutation was detected in 37 cases (44%). In the 37 mutated cases by NGS, the median proportion of mutated allele was 35% (range 3 to 99%), including a median of 72%, 35%, 25 % in AML, higher risk MDS and lower risk MDS with del 5q, respectively. The mutated clone size was lower than 10% in only 2 patients who both had lower risk MDS with del 5q (3 and 6%, respectively). A perfect correlation between FASAY and NGS was found in 80 (95.5%) cases. The 4 discordant cases included a mutation detected only by FASAY in 2 cases, and only by NGS in 2 cases. Undetected mutations by NGS were insertions of intronic sequences (intron 9) not explored by the technique used. These insertions resulted in non-functional protein well detected by FASAY which analyses the global cDNA sequence including splicing defects. Undetected mutations by FASAY were mutations in which the percentage of mutated alleles was less than 10% (3% and 6 % respectively). Finally, while the cost of NGS analysis for TP53 mutation is around 200 euros when performed alone (and around 2000 euros when combined to analysis of the 30 main other genes involved in MDS and AML), the cost of the FASAY technique is around 20 euros (prices including reagents only). Conclusion The FASAY technique is a cheap method, that in spite of a sensitivity of only 10%, was able to detect 98% of TP53 mutations detected by NGS. In fact those mutations appear to involve generally relatively large clones in MDS and AML. FASAY could also detect 2 atypical intronic mutations overlooked by NGS. Demonstrating in such difficult cases that the resulting p53 protein is non functional and therefore probably has pathophysiological significance, is an advantage of FASAY .The combination of the 2 methods, and especially the combination of DNA and RNA analysis, may be useful in such cases. Disclosures No relevant conflicts of interest to declare.


1997 ◽  
Vol 19 (1) ◽  
pp. 1-14 ◽  
Author(s):  
Brian M. Stecher ◽  
Stephen P. Klein

Estimates of the costs of including hands-on measures of science skills in large-scale assessment programs are drawn from a field trial involving more than 2,000 fifth- and sixth-grade students. These estimates include the resources needed to develop, administer, and score the tasks. They suggest that performance measures are far more expensive than typical multiple-choice tests for an equal amount of testing time, and the cost increases even further for an equally reliable score on an individual student. Because of the complexities of equipment and materials, hands-on measures in science are about three times more expensive than open-ended writing assessments. Alternative approaches to development and administration (such as using less expensive equipment and having the tasks administered by classroom teachers rather than trained Exercise Administrators) could reduce costs by up to 50%, but these practices may reduce the quality of the data obtained. However, including performance assessments in a state’s testing program may have many positive effects, including fostering standards-based educational reform and encouraging more effective teaching methods. The challenge is to determine whether these potential benefits actually exist and if they do, how they can be realized within the budget constraints of most testing programs.


Author(s):  
Varun Bhogal ◽  
Zornitza Genova Prodanoff ◽  
Sanjay P. Ahuja ◽  
Kenneth Martin

RFID (radio frequency identification) technology has gained popularity in a number of applications. Decreased cost of hardware components along with wide adoption of international RFID standards have led to the rise of this technology. One of the major factors associated with the implementation of RFID infrastructure is the cost of tags. RFID tags operating in the low frequency spectrum are widely used because they are the least expensive, but have a small implementation range. This paper presents an analysis of RFID performance across low frequency (LF), high frequency (HF), and ultra-high frequency (UHF) environments. The authors' evaluation is theoretical, using a passive-tag BFSA based simulation model that assumes 10 to 1,500 tags per reader and is created with OPNET Modeler 17. Ceteris paribus, the authors' results indicate that total census delay is lowest for UHF tags, while network throughput performance of LF tags is highest for large scale implementations of hundreds of tags in reader's range. A statistical analysis has been conducted on the findings for the three different sets.


Author(s):  
Rajashree Shettar ◽  
Vidya Niranjan ◽  
V. Uday Kumar Reddy

Invention of new computing techniques like cloud and grid computing has reduced the cost of computations by resource sharing. Yet, many applications have not moved completely into these new technologies mainly because of the unwillingness of the scientists to share the data over internet for security reasons. Applications such as Next Generation Sequencing (NGS) require high processing power to process and analyze genomic data of the order of petabytes. Cloud computing techniques to process this large datasets could be used which involves moving data to third party distributed system to reduce computing cost, but this might lead to security concerns. These issues are resolved by using a new distributed architecture for De novo assembly using volunteer computing paradigm. The cost of computation is reduced by around 90% by using volunteer computing and resource utilization is increased from 80% to 90%, it is secure as computation can be done locally within the organization and is scalable.


Author(s):  
Rajashree Shettar ◽  
Vidya Niranjan ◽  
V. Uday Kumar Reddy

Invention of new computing techniques like cloud and grid computing has reduced the cost of computations by resource sharing. Yet, many applications have not moved completely into these new technologies mainly because of the unwillingness of the scientists to share the data over internet for security reasons. Applications such as Next Generation Sequencing (NGS) require high processing power to process and analyze genomic data of the order of petabytes. Cloud computing techniques to process this large datasets could be used which involves moving data to third party distributed system to reduce computing cost, but this might lead to security concerns. These issues are resolved by using a new distributed architecture for De novo assembly using volunteer computing paradigm. The cost of computation is reduced by around 90% by using volunteer computing and resource utilization is increased from 80% to 90%, it is secure as computation can be done locally within the organization and is scalable.


Author(s):  
Shaun M. Purcell

There have been tremendous advances in the molecular technologies and data-analytic methods at our disposal for studying the genetic bases of complex d diseases and traits. These advances have enabled the creation of comprehensive catalogs of different forms of human genetic variation, as well as large-scale studies focused on specific diseases or traits. This chapter outlines the general principles behind some of these advances and discusses their application to studying complex genetic traits, with a focus on neuropsychiatric disease in particular. Different genetic strategies that are underway in psychiatric genetics include studies of de novo variation in exome sequencing, large deletion and duplication copy number variants, rare and low-frequency variants segregating in populations, and common polymorphisms.


Sign in / Sign up

Export Citation Format

Share Document