This study reports on the first use of an Affymetrix GeneChip 3'IVT expression array for discovering both sense- and antisense-strand transcription. Through the adaptation of the Affymetrix WT assay, the antisense transcribed strand was successfully labeled and hybridized to the Wheat Genome Array, which allowed for the detection of natural sense-antisense transcript pairs. To our knowledge, the Wheat Genome Array does not contain any probes for known sense-antisense transcript pairs, thus the data from the hybridizations could not be standardized and/or normalized to a known sense-antisense transcript pair. Subsequently, a highly stringent data acceptance threshold was applied, based on PMA call and expression value cutoffs. This increased the confidence in detecting true antisense transcription. It is important to recognize the limitations of this study, which stem from the 'closed' nature of microarray systems. Because the Wheat Genome Array contains only known transcript sequences, the study is clearly limited to detection of transcript pairs that are present on the array. Further, the probes for each transcript are biased to the 3' end of transcripts and do not span the entire gene. Thus, because antisense-strand transcripts commonly have a different splice structure they may not be detected. Subsequently the 110 candidate sense-antisense transcript pairs and the 80 potentially antisense-specific transcripts that were identified are likely to under-represent the number of true transcript pairs. In future studies, custom microarrays containing probes for sense and antisense transcripts would be useful as different target preparation assays would not be required, but because we aimed to obtain a broad representation of the extent of antisense transcription we chose to use the most comprehensive Wheat Genome Array.
The function of antisense-strand transcription is widely believed to regulate the expression of sense-strand transcripts at either transcription, mRNA maturation or translation [2
]. In fact, Lapidot and Pilpel [1
] reviewed the literature and postulated four mechanisms of action; transcriptional interference, RNA masking, double-stranded RNA (ds-RNA)-dependent mechanisms, and chromatin remodeling. The ds-RNA mechanisms would likely be the result of RNA-dependent RNA polymerases, which generate ds-RNA that are the precursors of short interfering RNA (siRNA). The timing of sense- and antisense-strand transcription is also important; for example, if the sense-strand is transcribed first up to a certain level followed by transcription of the antisense-strand, the biological result would be delayed inhibition of the sense-strand gene expression. Conversely, if the antisense-strand was transcribed first, this would result in pre-inhibition of sense-strand gene expression up to a threshold. Differences in the half-life of the sense-and antisense-strand transcripts, as well as tissue-specificity and potential light and/or diurnal transcript regulation [24
] would also affect these scenarios. In the present study the timing of transcription and relative level of sense- and antisense-transcripts could not be determined because a single time-point was used for RNA extraction in each tissue, and the design of the assay did not allow valid comparisons between the 3'IVT and WT results to estimate transcript levels. Thus the mode of action of the detected sense-antisense transcript pairs would require further study.
An important observation in this study was the functional annotation of the sense-antisense transcript pairs, which indicated a significant over-representation of those involved in energy production, particularly photosynthesis. Additionally, many transcripts for ribosomal proteins involved in protein synthesis were identified. The abundance of antisense transcripts for these common plant processes may indicate that they are negatively regulated by antisense transcripts. Alternatively, the antisense transcripts could possibly be the result of ectopic expression. There is little data on large-scale antisense transcription profiling in plants to compare these results with, but a study in rice of leaf and seed tissue using Serial Analysis of Gene Expression (SAGE) identified sense-antisense transcript pairs and also found that the most abundant pairs were annotated as involved in energy production, including RUBISCO and a Photosystem I protein [11
]. The similarity between studies shows that transcripts involved in photosynthesis are likely to be controlled by antisense transcripts in plants. An appealing explanation is the possibility for diurnal regulation of photosynthesis through antisense regulation. Although this study did not span a time-course required to demonstrate diurnal regulation, the results warrant further exploration of this hypothesis.
The results of the strand-specific RT-PCR also showed that antisense transcription is likely to be tissue-specific. Only one of the RT-PCR results was not in complete agreement with the microarray result, which could be due to truncated antisense transcripts where the priming sites were absent. In their microarray study of human cell antisense transcription, Ge et al
] found that 26% of the RT-PCR results were not consistent with microarray observations. In this study we also identified 80 transcripts as potentially antisense-specific, although further studies would be needed to confirm this because of the possibility for incorrectly oriented probes or strand bias during hybridization. The majority of these transcripts were annotated as unknown, but of those that were there was again a trend towards function in photosynthesis. A high percentage were also functionally involved in controlling transcription, including transcripts with homology to DNA-directed RNA polymerase, which indicates that gene expression in wheat may be regulated by antisense transcripts at the transcriptional level.
A recent study in wheat involving SAGE of developing grain also identified antisense transcripts [14
], where the most abundant functional categories aside from unknown tags were associated with storage and reproduction. The abundance of these functional categories was due to the sampling of developing grain tissue, while the abundance of energy-related transcripts in our study is most likely due to the selection of photosynthetic tissues. For this reason, these two studies complement each other well. As in our study, Poole et al
] found that most antisense tags were of unknown function and that many transcripts were highly expressed in both sense and antisense, which may suggest a function of the antisense transcript for mediating alternative polyadenylation rather than down-regulation of the sense transcript, although there is no evidence for this at this stage. One other similarity to our study was the identification by Poole et al
] of antisense transcripts related to transcription, such as nucleotide binding proteins, which the authors suggest may enable the control of multiple pathways that require large scale changes during development. Other than these similarities, the results of our study differ from Poole et al
], which again is likely due to the complementary tissues analyzed.
This study was exploratory and revealed that the method was successful in identifying sense-antisense transcript pairs using the commercial Wheat Genome Array. The next step from this study is to select potentially interesting antisense transcripts for further study. There were several transcript pairs belonging to functional categories including 'Cell death' and 'Transcription' that may be involved in the regulation of important biological processes, and the antisense-specific transcripts related to transcription are also of interest. An understanding of the role of antisense transcription as it relates to gene expression may be important for the expression of certain phenotypes of interest. Additionally, knowledge of natural antisense transcripts may also be important for altering gene expression through transgenic studies in plants. The abundance of antisense-strand transcripts in plants is supported by recent studies using 'open' transcriptomics systems including SAGE [11
] and Massively Parallel Signature Sequencing (MPSS) [12
]. With the advent of RNA-Seq (RNA sequencing), which is high-throughput transcriptome sequencing method [25
] that incorporates the use of next-generation sequence-by-synthesis technologies, the future will see a greatly enhanced discovery and understanding of antisense-strand transcription in plants.