genomic-bioinformatic analysis of transcripts enriched in the third-stage larva of the parasitic nematode ascaris suumgenomic-bioinformatic分析记录丰富的三级幼虫寄生线虫蛔虫suum.pdfVIP

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2017-09-01 发布于上海
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genomic-bioinformatic analysis of transcripts enriched in the third-stage larva of the parasitic nematode ascaris suumgenomic-bioinformatic分析记录丰富的三级幼虫寄生线虫蛔虫suum.pdf

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genomic-bioinformatic analysis of transcripts enriched in the third-stage larva of the parasitic nematode ascaris suumgenomic-bioinformatic分析记录丰富的三级幼虫寄生线虫蛔虫suum

Genomic-Bioinformatic Analysis of Transcripts Enriched in the Third-Stage Larva of the Parasitic Nematode Ascaris suum 1,2 3 3 4 5 Cui-Qin Huang , Robin B. Gasser *, Cinzia Cantacessi , Alasdair J. Nisbet , Weiwei Zhong , Paul W. 5 6 6 1 1 1 Sternberg , Alex Loukas , Jason Mulvenna , Rui-Qing Lin , Ning Chen , Xing-Quan Zhu * 1 Laboratory of Parasitology, College of Veterinary Medicine, South China Agricultural University, Guangzhou, Guangdong Province, People’s Republic of China, 2 College of Life Sciences, Longyan University, Fujian Province, People’s Republic of China, 3 Department of Veterinary Science, The University of Melbourne, Werribee, Victoria, Australia, 4 Parasitology Division, Moredun Research Institute, Penicuik, United Kingdom, 5 Biology Division, California Institute of Technology, Pasadena, California, United States of America, 6 Helminth Biology Laboratory, Division of Infectious Diseases and Immunology, Queensland Institute of Medical Research, Brisbane, Queensland, Australia Abstract Differential transcription in Ascaris suum was investigated using a genomic-bioinformatic approach. A cDNA archive enriched for molecules in the infective third-stage larva (L3) of A. suum was constructed by suppressive-subtractive hybridization (SSH), and a subset of cDNAs from 3075 clones subjected to microarray analysis using cDNA probes derived from RNA from different developmental stages of A. suum. The cDNAs (n = 498) shown by microarray analysis to be enriched in the L3 were sequenced and subjected to bioinformatic analyses using a semi-automat