A database to aid probe design for virus identification

Viral infection poses a major problem for public health, horticulture and animal husbandry, possibly causing severe health crises and economic loss. Viral infections can be identified by the specific detection of viral sequences in two ways, the first is the amplification-based method, such as using the polymerase chain reaction (PCR), the reverse transcription-polymerase chain reaction (RT-PCR), or nested-PCR, for example, and the second is the hybridization-based approach, such as the use of southern blotting, northern blotting, dot blotting and DNA chips. The former provides the advantages of fast and specific detection and a lower detection limit, but also has some the following weakness; (1) the clinicians must assess which viruses are suspected in an infectious event; (2) the nucleotides on the nearest 3'-end of the designed primers are very important to the successful of the extension of the primer; (3) although multiplex PCR can be used to detect many viral sequences simultaneously, diagnosing the viral sequences of over 20 different species or strains in a single reaction is currently very difficult. The hybridization-based method can not only tolerate sequence variations of newly evolved virus strains, but can also simultaneously diagnose more viral sequences in a single reaction than can multiplex PCR. Many chips have so fat been designed for clinical use. Most are designed for special purpose, such as typing enterovirus infection, and compare fewer than 30 different viral sequences. None considers all primer design, increasing the likelihood of cross hybridization of similar sequences with other viral sequences. To prevent this possibility, this work establishes a platform and database that provides users with specific probes of all known viral genome sequences, to designing their diagnostic chips. This work develops a system for designing probes online. A user can select any number of different viruses and set their experimental conditions. Including, for example, melting temperature, length of probe. The system then return the optimal sequences to suspected viral infections to be automatically identified from database. The system that supports probe design for identifying virus has been published on our web page http://bioinfo.csie. ncu.edu.tw.