Improving high-resolution copy number variation analysis from next generation sequencing using unique molecular identifiers

• Published in: BMC bioinformatics Vol. 22; no. 1; p. 120
• Main Authors: Viailly, Pierre-Julien, Sater, Vincent, Viennot, Mathieu, Bohers, Elodie, Vergne, Nicolas, Berard, Caroline, Dauchel, Hélène, Lecroq, Thierry, Celebi, Alison, Ruminy, Philippe, Marchand, Vinciane, Lanic, Marie-Delphine, Dubois, Sydney, Penther, Dominique, Tilly, Hervé, Mareschal, Sylvain, Jardin, Fabrice
• Format: Journal Article
• Language: English
• Published: England BioMed Central Ltd 12.03.2021; BioMed Central; BMC
• Subjects: Adult; Algorithms; Amplification; B-cell lymphoma; Bioinformatics; Cell activation; CNV calling; Comparative Genomic Hybridization; Computer Science; Copy number; Copy number variations; Cytogenetics; Deoxyribonucleic acid; DNA; DNA Copy Number Variations; DNA sequencing; Gain; Gene deletion; Genes; Genetic research; Genomes; High-Throughput Nucleotide Sequencing; Humans; Hybridization; Inactivation; Lymphocytes B; Lymphoma; Male; Methodology; Methods; Middle Aged; Next generation sequencing; Nucleotide sequence; Nucleotide sequencing; Nucleotides; Prospective Studies; Segmentation; Sequence Analysis, DNA; Sequences; Statistical inference; Statistical methods; Tumor cells; Tumor suppressor genes; Tumors; UMI; France; UMI; Next generation sequencing; CNV calling
• ISSN: 1471-2105; 1471-2105
• DOI: 10.1186/s12859-021-04060-4

Recently, copy number variations (CNV) impacting genes involved in oncogenic pathways have attracted an increasing attention to manage disease susceptibility. CNV is one of the most important somatic aberrations in the genome of tumor cells. Oncogene activation and tumor suppressor gene inactivation are often attributed to copy number gain/amplification or deletion, respectively, in many cancer types and stages. Recent advances in next generation sequencing protocols allow for the addition of unique molecular identifiers (UMI) to each read. Each targeted DNA fragment is labeled with a unique random nucleotide sequence added to sequencing primers. UMI are especially useful for CNV detection by making each DNA molecule in a population of reads distinct. Here, we present molecular Copy Number Alteration (mCNA), a new methodology allowing the detection of copy number changes using UMI. The algorithm is composed of four main steps: the construction of UMI count matrices, the use of control samples to construct a pseudo-reference, the computation of log-ratios, the segmentation and finally the statistical inference of abnormal segmented breaks. We demonstrate the success of mCNA on a dataset of patients suffering from Diffuse Large B-cell Lymphoma and we highlight that mCNA results have a strong correlation with comparative genomic hybridization. We provide mCNA, a new approach for CNV detection, freely available at https://gitlab.com/pierrejulien.viailly/mcna/ under MIT license. mCNA can significantly improve detection accuracy of CNV changes by using UMI.