Abstract Detail

Sequence-based Identification of Fungi

Porras-Alfaro, Andrea [1], Liu, Kuan-Liang  [2], Xie , Gary [3], Cole, James R. [4], Kuske, Cheryl R [3].

RDP Classifier: ITS and LSU Automated Fungal Identification.

Next generation sequencing has created new opportunities to study the structure, biogeographical patterns, and ecology of fungal communities, among many other aspects of fungal biology. This wealth of information also represents new challenges to identify fungi that are not yet cultured and thus only represented by sequence data. We analyzed and compared the relevance of curated databases, fragment size, and the use of a bootstrap cutoff in automated fungal classification for the ITS and LSU regions of the fungal rRNA operon. Classification accuracy of a naïve Bayesian classifier and BLASTN were also compared for both regions. Small differences were observed for the accuracy of ITS1, ITS2 and LSU regions, and classification accuracy was affected by short sequence length and the use of bootstrap cutoff. Our comparisons showed that the LSU and ITS both represent useful markers for automated fungal classification to the genus level. The quality of the reference database had a major impact on accuracy of fungal classification. The improvement in fungal classification will greatly benefit of the definition of clear guidelines to remove taxonomic inconsistences and the inclusion of taxa represented solely by environmental sequences in reference databases. The potential of the fungal classifier as a tool to facilitate classification and the incorporation of environmental data into curated reference databases will be discussed.

Related Links:
RDP classifier
Porras-Alfaro Lab

1 - Western Illinois University, Biological Sciences, Waggoner Hall 372, 1 University Circle, Macomb, IL, 61455, USA
2 - National Cheng Kung University, Institute of Information Management, Taiwan, Republic of China
3 - Los Alamos National Laboratory, Bioscience Division, Los Alamos, NM, USA
4 - Michigan State University, Center for Microbial Ecology, East Lansing, MI, USA

Keywords:
RDP Classifier
ITS rRNA
LSU rRNA
Automated Classification.

Presentation Type: Symposium or Colloquium Presentation
Session: SY8
Location: Room 103 AB/Kellogg Hotel and Conference Center
Date: Wednesday, June 11th, 2014
Time: 3:00 PM
Number: SY8005
Abstract ID:133
Candidate for Awards:None