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Potato Expression Profile Platform Construction And Application

Posted on:2016-08-10Degree:MasterType:Thesis
Country:ChinaCandidate:S S ZhangFull Text:PDF
GTID:2283330461990293Subject:Vegetable science
Abstract/Summary:PDF Full Text Request
Potato(Solanum tuberosum L.) is the fourth largest food crop in the world, inferior to rice, wheat and maize. The potato genome sequence was published in 2011, which laid a good foundation to study potato molecular biology. With the constant improvement of sequencing technologies, the data of potato biological information are also booming, but these data were lack of reasonable integration and efficient use. It is very necessary to know how to integrate these data and establish a platform to exchange data, which is extraordinarily significant for potato breeding and improvement.Here we performed our study based on the RNA-Seq data of potato lines 10908-06, E26, E3, ACL-27, Longshu 3 and Russet Burbank with various treatments. Using the published genome sequence of potato DM1-3 as a reference genome, we also did do novo assembling to analyze the unmapped data. Finally we have built a genome browser named Gbrowse as well as databases for the expression profiles and the BLAST querying, and found 6416 new transcripts matched onto the DM1-3 genome, and 1610 transcripts unmatched onto the DM1-3 genome. Using the integrated data, finally we got in total 84473 transcripts assigned as pan transcriptome HZAU_potato_pan-trans V1.0. Gene integration was performed by combining all known genome sequence data, which results in the combining support HZAU_potato V1.0. RNA-Seq data were mapped to both HZAU_potato V1. 0 and DM1-3 genome. Results show that the match rate of HZAU_potato V1.0 increases about 0.8%. Gene annotation was based on the results obtained from different softwares, e.g. ab initio prediction, homology searches and CPC. Besides, 484 transcripts with no apparent coding capacity show similarity to non-coding RNA or mi RNAs. Furthermore, we also analyzed SNPs among the six different genotypes, finally show that ACL-27 has the farthest genetic relationship, 10908-06 and E26 have the nearest genetic relationship. Meanwhile the transcript abundance in various chromosomes by the integrated databases show that reads have the hither coverage on both ends of the chromosome, and lower coverage in the central.To summarize, we analyzed the transcription of different potato genotypes under different conditions, and discovered new unknown transcripts and SNPs. These results further enrich the potato database, and the potato database provide an easy platform to study potato biology and inquire related important information.
Keywords/Search Tags:Potato, Database, RNA-Seq, Transcriptome, Functional annotation
PDF Full Text Request
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