Abstract
BackgroundNext-generation transcriptome sequencing (RNA-Seq) has become the standard practice for studying gene splicing, mutations and changes in gene expression to obtain valuable, accurate biological conclusions. However, obtaining good sequencing coverage and depth to study these is impeded by the difficulties of obtaining high quality total RNA with minimal genomic DNA contamination. With this in mind, we evaluated the performance of Phenol-free total RNA purification kit (Amresco) in comparison with TRI Reagent (MRC) and RNeasy Mini (Qiagen) for the extraction of total RNA of Pseudomonas aeruginosa which was grown in glucose-supplemented (control) and polyethylene-supplemented (growth-limiting condition) minimal medium. All three extraction methods were coupled with an in-house DNase I treatment before the yield, integrity and size distribution of the purified RNA were assessed. RNA samples extracted with the best extraction kit were then sequenced using the Illumina HiSeq 2000 platform.ResultsTRI Reagent gave the lowest yield enriched with small RNAs (sRNAs), while RNeasy gave moderate yield of good quality RNA with trace amounts of sRNAs. The Phenol-free kit, on the other hand, gave the highest yield and the best quality RNA (RIN value of 9.85 ± 0.3) with good amounts of sRNAs. Subsequent bioinformatic analysis of the sequencing data revealed that 5435 coding genes, 452 sRNAs and 7 potential novel intergenic sRNAs were detected, indicating excellent sequencing coverage across RNA size ranges. In addition, detection of low abundance transcripts and consistency of their expression profiles across replicates from the same conditions demonstrated the reproducibility of the RNA extraction technique.ConclusionsAmresco’s Phenol-free Total RNA purification kit coupled with DNase I treatment yielded the highest quality RNAs containing good ratios of high and low molecular weight transcripts with minimal genomic DNA. These RNA extracts gave excellent non-biased sequencing coverage useful for comprehensive total transcriptome sequencing and analysis. Furthermore, our findings would be useful for those interested in studying both coding and non-coding RNAs from precious bacterial samples cultivated in growth-limiting condition, in a single sequencing run.Electronic supplementary materialThe online version of this article (doi:10.1186/s13104-015-1726-3) contains supplementary material, which is available to authorized users.
Highlights
Next-generation transcriptome sequencing (RNA-Seq) has become the standard practice for studying gene splicing, mutations and changes in gene expression to obtain valuable, accurate biological conclusions
Since DNA is usually co-extracted during the RNA isolation procedures, evaluating the presence of contaminating genomic DNA and removal of these molecules using DNase I treatment is a must for RNA samples prior to sequencing
We found that 452 of these peaks in the intergenic regions coincided with the small RNA (sRNA) discovered by Gómez-Lozano et al [36] who performed an elaborate sRNA sequencing study of P. aeruginosa PAO1 grown in LB broth [36]
Summary
Next-generation transcriptome sequencing (RNA-Seq) has become the standard practice for studying gene splicing, mutations and changes in gene expression to obtain valuable, accurate biological conclusions. Obtaining good sequencing coverage and depth to study these is impeded by the difficulties of obtaining high quality total RNA with minimal genomic DNA contamination. With this in mind, we evaluated the performance of Phenol-free total RNA purification kit (Amresco) in comparison with TRI Reagent (MRC) and RNeasy Mini (Qiagen) for the extraction of total RNA of Pseudomonas aeruginosa which was grown in glucose-supplemented (control) and polyethylene-supplemented (growth-limiting condition) minimal medium. To identify what confers the pathogenicity and/or ability to synthesize value-added products, one must know the changes at the metabolic level and understand the underlying molecular mechanisms in the bacterial cells Obtaining these valuable biological and molecular insights into the transcriptome of bacterial cells is possible with the introduction of next-generation sequencing (NGS) platforms that perform massive parallel sequencing. RNASeq has become the “gold standard” for annotation of transcripts and differential gene expression analysis as the output can be efficiently mapped to the genome and the expression of each transcript can be quantified by digitally recording how frequently they are represented in a sequenced sample [8,9,10]
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