Transcriptomic Analysis of Nematode Trapping-Fungi for Gene Discovery and Differential Expression Assessment

• Main Authors: Chieh Wang, 王 捷
• Other Authors: Shean-Shong Tzean
• Format: Others
• Language: zh-TW
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/ktdf9e

碩士 === 國立臺灣大學 === 植物病理與微生物學研究所 === 100 === Nematode-trapping fungi (NTF) can capture nematodes with varied trapping advices, thus possess potential as biocontrol agent to control parasitic nematodes. Nevertheless, to fulfill this purpose, a thorough understanding of the underlying mechanism to account for the ecological adaption, survival, parasitic and colonizing capability is crucial. In light of the modern rapid advancement of molecular biology and biotechnology, i.e. the next generation whole genome sequencing technique, a completely different revolutionary vision in elucidation of the nematode-trapping fungi interactions becomes feasible. In this study, we focused on de-novo genes discovery in order to correlate to trapping and colonization capability, and evolutionary hierarchy of NTF. We constructed transcriptomes of six representative NTF：Arthrobotrys musiformis (adhesive networks), Arthrobotrys brochopaga (constructing ring), Dactylella formosana (adhesive knobs), Dactyllela leptospora (adhesive knobs and non-constructing ring), Monacrosporium cionopagum (adhesive column), Monacrosporium phymatopagum (sessile adhesive knobs) without or with nematode amendment and incubation for 24, 48 hrs, respectively. The constructed cDNA libraries were read by Illumina/Solexa HiSeqTM 2000 sequencing system, then sequences assembled, annotated and function analyzed. The significantly up-regulated and down-regulated genes were subject to comparison between or among transcriptomes. Several genes suspected to comply with the purpose mentioned above were acessed and proceeded for in-depth analysis, including protein database blasting, prediction, metabolic pathway assessment and putative functional analysis. Comparative transcriptomes analysis revealed that some genes were significantly up-regulated in all NTF, such as phosphorylase, cell surface glycoprotein, large adhesion, peroxisome and molecular involved in recognition. The immense bioinformatics came up from this study actually established a useful platform for perspective study.