EOSAL-CNV for Easy and Rapid Detection of CNVs by Fragment Analysis : EOSAL: A Fast and Reliable New Method for CNV Detection.

Copy number variations (CNVs) are a type of genetic variation involving from 50 base pairs (bps) to millions of bps and, in a general point of view, can include alterations of complete chromosomes. As CNVs mean the gain or loss of DNA sequences, their detection requires specific techniques and analysis. We have developed Easy One-Step Amplification and Labeling for CNV Detection (EOSAL-CNV) by fragment analysis in a DNA sequencer. The procedure is based on a single PCR reaction for amplification and labeling of all fragments included. The protocol includes specific primers for the amplification of the regions of interest with a tail in each of the primers (one for forward and another for the reverse primers) together with primers for tail amplification. One of the primers for tail amplification is labeled with a fluorophore, allowing the amplification and labeling in the same reaction. Combination of several tail pairs and labels allows the detection of DNA fragment by different fluorophores and increases the number of fragments that can be analyzed in one reaction. PCR products can be analyzed without any purification on a DNA sequencer for fragment detection and quantification. Finally, simple and easy calculations allow the detection of fragments with deletions or extra copies. The use of EOSAL-CNV allows simplifying and reducing costs in sample analysis for CNV detection.

Easy One-Step Amplification and Labeling Procedure for Copy Number Variation Detection.

BACKGROUND: The specific characteristics of copy number variations (CNVs) require specific methods of detection and characterization. We developed the Easy One-Step Amplification and Labeling procedure for CNV detection (EOSAL-CNV), a new method based on proportional amplification and labeling of amplicons in 1 PCR. METHODS: We used tailed primers for specific amplification and a pair of labeling probes (only 1 labeled) for amplification and labeling of all amplicons in just 1 reaction. Products were loaded directly onto a capillary DNA sequencer for fragment sizing and quantification. Data obtained could be analyzed by Microsoft Excel spreadsheet or EOSAL-CNV analysis software. We developed the protocol using the LDLR (low density lipoprotein receptor) gene including 23 samples with 8 different CNVs. After optimizing the protocol, it was used for genes in the following multiplexes: BRCA1 (BRCA1 DNA repair associated), BRCA2 (BRCA2 DNA repair associated), CHEK2 (checkpoint kinase 2), MLH1 (mutL homolog 1) plus MSH6 (mutS homolog 6), MSH2 (mutS homolog 2) plus EPCAM (epithelial cell adhesion molecule) and chromosome 17 (especially the TP53 [tumor protein 53] gene). We compared our procedure with multiplex ligation-dependent probe amplification (MLPA). RESULTS: The simple procedure for CNV detection required 150 min, with <10 min of handwork. After analyzing >240 samples, EOSAL-CNV excluded the presence of CNVs in all controls, and in all cases, results were identical using MLPA and EOSAL-CNV. Analysis of the 17p region in tumor samples showed 100% similarity between fluorescent in situ hybridization and EOSAL-CNV. CONCLUSIONS: EOSAL-CNV allowed reliable, fast, easy detection and characterization of CNVs. It provides an alternative to targeted analysis methods such as MLPA.

MuffinInfo: HTML5-Based Statistics Extractor from Next-Generation Sequencing Data.

Usually, the information known a priori about a newly sequenced organism is limited. Even resequencing the same organism can generate unpredictable output. We introduce MuffinInfo, a FastQ/Fasta/SAM information extractor implemented in HTML5 capable of offering insights into next-generation sequencing (NGS) data. Our new tool can run on any software or hardware environment, in command line or graphically, and in browser or standalone. It presents information such as average length, base distribution, quality scores distribution, k-mer histogram, and homopolymers analysis. MuffinInfo improves upon the existing extractors by adding the ability to save and then reload the results obtained after a run as a navigable file (also supporting saving pictures of the charts), by supporting custom statistics implemented by the user, and by offering user-adjustable parameters involved in the processing, all in one software. At the moment, the extractor works with all base space technologies such as Illumina, Roche, Ion Torrent, Pacific Biosciences, and Oxford Nanopore. Owing to HTML5, our software demonstrates the readiness of web technologies for mild intensive tasks encountered in bioinformatics.