Consequently, clean reference databases as well as automated phyl

Consequently, clean reference databases as well as automated phylogenetic assignment and analysis methods are critical needs. Purposes of the Meeting This meeting was organized in order to: JQ1 supplier Facilitate communication, potential data exchange, and collaboration with the aim of improving fungal ITS sequence resources for the research community. Identify suitable ITS primers for fungal community analyses using ultra-high-throughput sequencing. Develop strategies for automated (and manual) database curation as well as the naming of environmental sequences and OTUs at various levels of resolution. Establish a sustainable plan for reference database development and maintenance. Participants The meeting participants included researchers representing publicly available databases that contain microbial sequence data (e.

g., GenBank, GreenGenes, RDP, SILVA) or fungi-specific resources (e.g., MycoBank, UNITE), as well as researchers currently using ultra-high-throughput sequencing to examine fungal communities or those involved in developing software, such as QIIME [12] and PhyloSift [13], to facilitate such studies. Activities The meeting was conducted as a two-day workshop. The first day was devoted primarily to brief presentations by participants outlining their involvement in curating public sequence databases, developing high-throughput sequencing pipelines, or using ultra-high-throughput sequencing to examine fungal diversity in environmental samples (e.g., air or soil). The presentations are available online [14].

The second day focused on discussions related to the assembly of a high-quality reference database of fungal ITS sequences, selecting ITS primers suitable for ultra-high-throughput sequencing, as well as methods to link ITS sequences to the fungal phylogeny for automated curation, quality control, and phylogeny-based community analysis methods. Conclusions / Outcomes Ultra-high-throughput sequence processing/analytical pipelines, such as those implemented in QIIME, rely on de-replication of large sequence datasets through clustering for the creation of reference sequence sets that can be used to assist in the recognition of OTUs from environmental samples. The meeting participants largely supported the use of the UNITE database [15,16] as a focal point for the development of high quality fungal ITS reference sequence sets.

UNITE currently has implemented several desirable features for this task, including: A comprehensive set of approximately 300,000 fungal ITS sequences extracted from public databases. An annotation management system (PlutoF) that allows qualified third-party users to add pertinent metadata (e.g., on ecology or geography), improve the taxonomic GSK-3 resolution, tag problematic entries, or correct misidentifications for sequences in the UNITE database.

Leave a Reply

Your email address will not be published. Required fields are marked *

*

You may use these HTML tags and attributes: <a href="" title=""> <abbr title=""> <acronym title=""> <b> <blockquote cite=""> <cite> <code> <del datetime=""> <em> <i> <q cite=""> <strike> <strong>