Abstract
Recent advancements in sequencing technologies have decreased both time span and cost for sequencing the whole bacterial genome. High-throughput Next-Generation Sequencing (NGS) technology has led to the generation of enormous data concerning microbial populations publically available across various repositories. As a consequence, it has become possible to study and compare the genomes of different bacterial strains within a species or genus in terms of evolution, ecology and diversity. Studying the pan-genome provides insights into deciphering microevolution, global composition and diversity in virulence and pathogenesis of a species. It can also assist in identifying drug targets and proposing vaccine candidates. The effective analysis of these large genome datasets necessitates the development of robust tools. Current methods to develop pan-genome do not support direct input of raw reads from the sequencer machine but require preprocessing of reads as an assembled protein/gene sequence file or the binary matrix of orthologous genes/proteins. We have designed an easy-to-use integrated pipeline, NGSPanPipe, which can directly identify the pan-genome from short reads. The output from the pipeline is compatible with other pan-genome analysis tools. We evaluated our pipeline with other methods for developing pan-genome, i.e. reference-based assembly and de novo assembly using simulated reads of Mycobacterium tuberculosis. The single script pipeline (pipeline.pl) is applicable for all bacterial strains. It integrates multiple in-house Perl scripts and is freely accessible from https://github.com/Biomedinformatics/NGSPanPipe.
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Acknowledgments
PK and AK acknowledge the financial support from Indian Council of Medical Research. UK thanks the UGC for grant of the fellowship. The authors thank Dr. Amit Katiyar for discussions. PK is grateful for the invitation to present her work at the ‘Second International Conference on Infectious Diseases and Nanomedicine—2015’ held during 15–18 December 2015 in Kathmandu, Nepal.
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Kulsum, U., Kapil, A., Singh, H., Kaur, P. (2018). NGSPanPipe: A Pipeline for Pan-genome Identification in Microbial Strains from Experimental Reads. In: Adhikari, R., Thapa, S. (eds) Infectious Diseases and Nanomedicine III. Advances in Experimental Medicine and Biology, vol 1052. Springer, Singapore. https://doi.org/10.1007/978-981-10-7572-8_4
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DOI: https://doi.org/10.1007/978-981-10-7572-8_4
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