Untangling the transcriptome from fungus-infected plant tissues

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• 作者：Sheng Zhu^a ; ¹ ; Yong-Mei Dai^b ; Xin-Ye Zhang^a ; ^c ; Jian-Ren Ye^b ; Ming-Xiu Wang^a ; Min-Ren Huang^a ; ^{njmrhuang@njfu.edu.cn}
• 关键词：bp ; Base pairs ; EST ; Expressed sequence tag ; Gb ; Gigabases ; hpi ; Hour post inoculation ; IGV ; Integrative Genomics Viewer ; Mb ; Megabases ; NGS ; Next-generation sequencing ; ORF ; Open reading frame ; PE1 ; paired-end library 1 ; PE2 ; paired-end library 2 ; PSA ; P
• 刊名：Gene
• 出版年：2013
• 出版时间：1 May, 2013
• 年：2013
• 卷：519
• 期：2
• 页码：238-244
• 全文大小：753 K

文摘

The development of sequencing technology allows low-cost generation of sequence data. The huge amount of raw sequence data now available has introduced many challenges associated with analysis of these large-scale data banks. For example, it is very important to distinguish materials of plant and fungal origin in fungus-infected plant tissue. The origin of transcripts that were sequenced from Library 895-M6 (poplar tissue infected by Marssonina brunnea) on Illumina/Solexa GA IIx was determined by combining three methods: (1) based on the taxonomic information of homologous sequences; (2) based on the reference genome sequence; (3) based on the transcriptome sequence of the host and its pathogen obtained from Library 895 (poplar) and Library M6 (M. brunnea) as well as Library 895-M6 (mixture of poplar and M. brunnea). We idenified accurately the origin of 80,978 (99.5 % ) contigs in the mixed poplar and M. brunnea sample (Library 895-M6) by integrating the results from the three methods. The results of this study demonstrate that a combination of these three approaches described here is an effective strategy for determining the origin of sequences in a mixed pool, and provides a basis for further transcriptome analysis of the mixed sample.