Identification of Fungal Gene Sequence Contamination in Transcriptome Sequence Data of Endangered Molluscs using Bioinformatics
Dae Kwon Song, Hyeon Jin Park, Min Kyu Sang, Jie Eun Park, Jun Yang Jeong, Chan-Eui Hong, Yong Tae Kim, Hyeon Jun Shin, Ziwei Liu, Yong Hoon Jo,Yeon Soo Han, Yong Seok Lee and Jong Soo Chang
Department of Biology, College of Natural Sciences, Soonchunhyang University, Asan, Chungnam 31538, Korea Korea Native Animal Resources Utilization Convergence Research Institute research Support Center (Core-Facility) for Bio-Bigdata Analysis and Utili
The amount of data is growing very fast as advances in NGS technology enable the acquisition of large amounts of genome and transcript-xome data. Moreover, the accuracy and speed of bioinformatic analysis of NGS data remains of great importance these days. However, the sequence database of mollusks is fall short of other organisms groups, and it thus appears that the annotation results after BLAST analysis are not accurate and reliable due to potential contamination with fungal sequences in mollusks sequence database. In this context, we constructed a BLAST database with 20 species of mollusk unigene sequences and 32 species of fungal sequences derived from previous studies. In order to confirm the contamination of fungal gene sequences in the unigenes of 20 endangered species, bioinformatics analysis was performed using BLAST. It reveals that the NGS sequences of mollusks are mixed with fungal sequences. Taken together, our results suggest that it is essential to reconfirm mollusks sequence information before publication.
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