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Next-generation Sequencing of 16S Ribosomal RNA Gene Amplicons
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Data analysis for 16S microbial profiling from different benchtop sequencing platforms.

Victor S Pylro1, Luiz Fernando W Roesch2, Daniel K Morais1

  • 1Microbiology Department, Universidade Federal de Viçosa, Viçosa, MG 36570-900, Brazil; AgroEcology Department, Rothamsted Research, Harpenden, Herts AL52JQ, United Kingdom.

Journal of Microbiological Methods
|September 7, 2014
PubMed
Summary
This summary is machine-generated.

Different next-generation sequencing (NGS) technologies yield consistent microbial ecology findings. Applying strict quality control and robust clustering ensures reliable results across diverse sequencing platforms.

Keywords:
Alpha diversityAmpliconsBeta diversityMicrobial community analysisNext generation sequencing

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Area of Science:

  • Microbial Ecology
  • Bioinformatics
  • Genomics

Background:

  • Evaluating microbial ecology studies is challenging due to variations in sequencing methodologies.
  • Inconsistent results hinder the comparison of data generated by different next-generation sequencing (NGS) technologies.

Purpose of the Study:

  • To investigate whether different NGS technologies can produce comparable results in microbial ecology.
  • To identify key factors influencing the consistency of sequencing data.

Main Methods:

  • Comparison of data from multiple NGS platforms.
  • Application of stringent sequence quality filtering protocols.
  • Utilization of accurate clustering algorithms for sequence analysis.

Main Results:

  • Consistent biological conclusions were achieved across different NGS technologies.
  • Stringent quality filtering and accurate clustering were critical for data comparability.
  • Methodological variations did not impede the attainment of similar ecological insights.

Conclusions:

  • The choice of NGS technology is less critical than data processing for microbial ecology.
  • Standardized bioinformatics pipelines, including quality filtering and clustering, are essential for reproducible microbial ecology research.