In any organism, transcriptomics is a potent tool for deciphering gene architecture and RNA-based control. Transcriptome research enables a bird's-eye perspective of selected phenomena in all genes at the same time, in contrast to the traditional "single gene" reductionist approach, in which biological phenomena are examined using a small collection of model genes. Transcriptomes were first studied in eukaryotes including humans, mice, flies, and yeast using millions of expressed sequence tags1 and, more recently, cDNA sequencing using ultra-high-throughput technology. Traditional beliefs on numerous RNA-based regulatory mechanisms have been challenged by the discovery of sequenced cDNAs: for example, alternative splicing now affects most human genes, and cis-antisense transcripts have been shown to overlap more than 10% of all protein-coding genes in metazoan genomes.
Despite the fact that whole-transcriptome research has been highly productive in eukaryotes for more than a decade, bacteria and archaea transcriptomes have been mostly ignored until recently. One reason is that prokaryotic transcriptomes were once thought to be simpler than eukaryotic transcriptomes; prokaryotic transcripts lack introns and are not alternatively spliced or edited, save in rare situations. Another key reason is that bacterial mRNAs lack the 3'-end poly(A) tail that distinguishes mature mRNAs in eukaryotes, making mRNA enrichment more difficult. Because ribosomal RNA and tRNA make up >95 percent of cellular RNA, transcriptome sequencing of non-enriched total RNA would give largely non-mRNA sequences.
It has recently been possible to analyze complete bacterial transcriptomes, thanks to a significant increase in sequencing capacity due to new sequencing technology, in combination with specialized mRNA enrichment and tiling array techniques. Many unexpected findings have been discovered in the first analyses of such transcriptomes, including a plethora of non-coding RNAs (ncRNAs), unique untranslated regulatory elements, and alternate operon architectures.
Figure 1. Flow diagram of the steps involved in microbial transcriptome sequencing. (Siezen, 2010)
New sequencing methods make it possible to sequence complete transcriptomes in high detail at a moderate cost. Total RNA is taken from the organism and reverse transcription is used to convert it to cDNA (RT). Alternative priming procedures are employed since bacterial mRNAs lack the poly(A) tail that is commonly used for RT priming in eukaryotic RNA–seq applications. Priming from a particular RNA probe ligated to mRNAs, oligo(dT) priming from intentionally polyadenylated mRNAs, and random hexamer priming are all examples.
At high density, genomic tiling arrays typically represent both strands of the genome. Following cDNA synthesis, the library is hybridized to the array, and signal intensities are used to infer expression. Unlike RNA–seq, mRNA enrichment is not required, and the experimental protocols are well-known. The array-based technique, on the other hand, requires hundreds of thousands of probes and is constrained by background noise and cross-hybridization, necessitating significant normalization. After normalization, the data can be used to infer contiguous transcription, just as RNA–seq can. The ideal tiling array would have probes beginning at each and every base in the genome; however, most tiling arrays have a lower density, owing to the high expense of the vast number of probes required. As a result, tiling array transcriptome maps are often lower resolution than RNA–seq transcriptome maps, which have a single-base-pair resolution. However, because prokaryotic genomes are relatively short, the tiling array approach is intriguing for future transcriptome research in other prokaryotes.
Although the subject of microbial transcriptomics is still in its early stages, it is obvious that it can help researchers better understand RNA-based regulatory processes across the genome. It is now possible to investigate the role of components such as ncRNAs, riboswitches, and cis-antisense regulators in the physiology and pathogenicity of any prokaryote using whole-transcriptome analysis.