Abstract
During the last few decades, most of microbiology laboratories have become familiar in analyzing Sanger sequence data for ITS barcoding. However, with the availability of next-generation sequencing platforms in many centers, it has become important for medical mycologists to know how to make sense of the massive sequence data generated by these new sequencing technologies. In many reference laboratories, the analysis of such data is not a big deal, since suitable IT infrastructure and well-trained bioinformatics scientists are always available. However, in small research laboratories and clinical microbiology laboratories the availability of such resources are always lacking. In this report, simple and user-friendly bioinformatics work-flow is suggested for fast and reproducible ITS barcoding of fungi.
Highlights
Since the introduction of Sanger Sequencing, many microbiology laboratories started using DNA sequence data for microbial identification and genotyping
We present a simple and easy bioinformatics workflow for one of the commonly asked questions, “what is the species of this fungal isolate”? The workflow consist of sequences quality check, de novo assembly and sequence similarity search
SIMPLE DATA ANALYSIS WORKFLOW: Regardless of next-generation sequencing (NGS) platform used, sequence data normally stored in text file in a Fastq format, which contains sequence data and the quality score of base calling for each base
Summary
Reviewed by: Jeanette Wagener, University of Aberdeen, UK Venkataramana M., DRDO-Bharathiar University Center for Life Sciences, India. Specialty section: This article was submitted to Fungi and Their Interactions, a section of the journal Frontiers in Microbiology. During the last few decades, most of microbiology laboratories have become familiar in analyzing Sanger sequence data for ITS barcoding. With the availability of next-generation sequencing platforms in many centers, it has become important for medical mycologists to know how to make sense of the massive sequence data generated by these new sequencing technologies. The analysis of such data is not a big deal, since suitable IT infrastructure and well-trained bioinformatics scientists are always available. In small research laboratories and clinical microbiology laboratories the availability of such resources are always lacking. Simple and user-friendly bioinformatics work-flow is suggested for fast and reproducible ITS barcoding of fungi
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