Abstract
Structural variants (SVs) such as deletions, duplications, insertions, or inversions are alterations in the human genome that may be linked to the development of human diseases. A wide range of technologies are currently available to detect and analyze SVs, but the restrictions of each of the methods are resulting in lower total accuracy. Over the past few years, the need to develop a reliable computational pipeline has arisen to merge and compare the SVs from various tools to get accurate SVs for downstream analysis. In this study, we performed a detailed analysis of long-read sequencing of the human genome and compared it with short-read sequencing using Illumina technology in terms of the distribution of structural variants (SVs). The SVs were identified in two families with three members each (mother, father, son) using fifteen independent SV callers. Then we utilized ConsensuSV algorithm to merge the results of these SVs callers to identify the reliable list of SVs for each member of the families. Furthermore, we studied the influence of SVs on chromatin interaction-based paired-end tags (PETs). Finally, while we compared the length and number-wise distribution between long-read-based and short-read-based SVs and their respective mapping on PETs. We conclude that SVs detected by our algorithm over sequencing data using ONT are superior compared to Illumina across all SV sizes and lengths, as well as the number of mapped to PETs.
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Acknowledgements
This work has been supported by National Science Centre, Poland (2019/35/O/ST6/02484 and 2020/37/B/NZ2/03757); Foundation for Polish Science co-financed by the European Union under the European Regional Development Fund (TEAM to DP). The work has been co-supported by European Commission Horizon 2020 Marie Skłodowska-Curie ITN Enhpathy grant “Molecular Basis of Human enhanceropathies” and National Institute of Health USA 4DNucleome grant 1U54DK107967-01 “Nucleome Positioning System for Spatiotemporal Genome Organization and Regulation.” Research was co-funded by Warsaw University of Technology within the Excellence Initiative: Research University (IDUB) programme. Computations were performed thanks to the Laboratory of Bioinformatics and Computational Genomics, Faculty of Mathematics and Information Science, Warsaw University of Technology using the Artificial Intelligence HPC platform financed by the Polish Ministry of Science and Higher Education (decision no. 7054/IA/SP/2020 of 2020-08-28).
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Chiliński, M. et al. (2023). Consensus-Based Identification and Comparative Analysis of Structural Variants and Their Influence on 3D Genome Structure Using Long- and Short-Read Sequencing Technologies in Polish Families. In: Basu, S., Kole, D.K., Maji, A.K., Plewczynski, D., Bhattacharjee, D. (eds) Proceedings of International Conference on Frontiers in Computing and Systems. Lecture Notes in Networks and Systems, vol 404. Springer, Singapore. https://doi.org/10.1007/978-981-19-0105-8_5
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DOI: https://doi.org/10.1007/978-981-19-0105-8_5
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