Related Experiment Video
Updated: Feb 1, 2026

Reconstruction of Single-Cell Innate Fluorescence Signatures by Confocal Microscopy
Published on: May 27, 2020
Cluster oligonucleotide signatures for rapid identification by sequencing
Manuel Zahariev1, Wen Chen2, Cobus M Visagie3
1Ottawa R&D Centre, Agriculture & Agri-Food Canada, 960 Carling Ave., Ottawa, ON, K1A 0C6, Canada. mz@alumni.sfu.ca.
Background:
Oligonucleotide signatures (signatures) have been widely used for studying microbial diversity and function in wet-lab settings, but using them for accurate in silico identification of organisms from high-throughput sequencing (HTS) data is only a proof of concept. Existing signature design programs for sequence signatures (signatures matching exactly one sequence) or clade signatures (signatures matching every sequence in a phylogenetic clade) are not able to identify all possible polymorphic sites for sequences with high similarity and perform poorly when handling large genome sequencing datasets.
Results:
We introduce cluster signatures: subsequences that match perfectly and exclusively any group of sequences in a data set. Cluster signatures provide complete recall for primer/probe design and increased discrimination between sequences beyond that of clade signatures. Using cluster signatures for in silico identification of HTS targets achieves good precision/recall and running time performance. This method has been implemented into an open source tool, the Automated Oligonucleotide Design Pipeline (adop), included in supplementary material and available at: https://bitbucket.org/wenchen_aafc/aodp_v2.0_release .
Conclusions:
Cluster signatures provide a rapid and universal analysis tool to identify all possible short diagnostic DNA markers and variants from any DNA sequencing dataset. They are particularly useful in discriminating genetic material from closely related organisms and in detecting deleterious mutations in highly or perfectly conserved genomic sites.
More Related Videos
Related Concept Videos
Cluster Sampling Method
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
Vesicular Tubular Clusters
With the help of motor proteins such...
Cis-regulatory Sequences
Sequences
Sanger Sequencing
Arithmetic Sequences

