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Jul 1, 2013 (Vol. 33, No. 13)

Unraveling the Transcriptome

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    Liver RNA from rats exposed to Aflatoxin B1 was analyzed by RNA-Seq or microarray: Reads from the Akr7a3 transcript (7-exon gene) show amount of added information compared to a single microarray probe. [National Institute of Environmental Health Sciences and PLoS One.]

    “The power of RNA-seq is that we can use it to visualize complex molecular signatures,” says B. Alex Merrick, Ph.D., group leader of the Molecular Toxicology and Informatics Group at the National Institute of Environmental Health Sciences.

    Dr. Merrick and colleagues recently illustrated this in an analysis exploring the impact of subchronic aflatoxin B1 exposure on the male rat liver transcriptome. Aflatoxin B1, classified as a group A carcinogen by the World Health Organization, is synthesized by certain Aspergillus species. Causally linked to hepatocellular carcinoma, this toxin is still a significant public health concern worldwide, particularly in developing countries.

    In a comparison to transcriptome profiles obtained with RNA-seq and microarray analyses, Dr. Merrick and colleagues reported that an increased number of differentially expressed transcripts can be visualized with RNA-seq. A key finding was that 49 differentially expressed transcripts were changed upon aflatoxin exposure.

    “These transcripts would not have been captured, had we relied solely on microarray data,” Dr. Merrick says. Two of these transcripts, which appear to originate from new, previously unannotated genes, were induced 10- to 25-fold, respectively, as a result of exposure. Investigators in Dr. Merrick’s group cloned one transcript, HafT1 (hepatic aflatoxin transcript 1) and reported that it appears to correspond to a unique gene, for which no corresponding ESTs were previously identified. HafT1, induced into visibility by aflatoxin exposure, lies within an exon of a transcription factor (ortholog to mouse Tcf7l1), but it is transcribed in the opposite direction.

    “There are so many unique features about this gene, and we would not have been able to capture them by using microarrays,” Dr. Merrick says.

    A relevant aspect of this experimental strategy is that the 90-day 1 ppm exposure that was employed in the analysis provided an opportunity to examine chemical carcinogenesis under conditions that mimic chronic, low-dose human toxicity. “This is a reasonable surrogate for human exposure,” says Dr. Merrick.

    While liver tumors can form over time at this exposure level, no malignancies or advanced tissue necrosis were observed in the study. Several of the differentially regulated transcripts were related to the function of kinetochore components, which are involved in cell division. These molecular changes, in all likelihood, would not have been captured with the more pronounced histological damage that generally occurs at higher doses. This illustrates the ability of RNA-seq to reveal very early molecular changes that occur during tissue remodeling, at stages that precede histological damage and tumor formation, and the strategy emerges as a promising tool to dissect molecular and cellular pathways affected by other toxins.

  • Transcriptomics Meets Proteomics

    “It is exciting to perform RNA-seq analysis on the same sample on which proteomics was done,” says Lloyd M. Smith, Ph.D., professor of chemistry at the University of Wisconsin-Madison.

    One of the challenges accompanying mass spectrometry-based analyses is that human proteomic databases, despite being frequently updated, do not reflect cell-to-cell variation in the multiple protein forms that are found in various cell and tissue types.

    Two major approaches have been implemented and are broadly used in proteomics. Bottom-up proteomics, which involves the enzymatic digestion of proteins into fragments that are subsequently identified by mass spectrometry, is technically more amenable, and the data are easier to interpret than in top-down proteomics, which involves the ionization and mass spectrometry analysis of intact proteins.

    While bottom-up proteomics offers higher sensitivity, it is not informative about the context where the peptides originated from, such as alternatively spliced or post-translationally modified protein products.“There are a lot of things that get lost during bottom-up proteomics,” Dr. Smith says.

    A new concept that Dr. Smith and colleagues introduced, that of proteoforms, is used to refer to all the molecular forms that the protein product of a single gene can be found in.

    This term, capturing a new layer of complexity thus far mostly overlooked, would ensure that protein changes resulting from coding single nucleotide polymorphisms and mutations, post-translational modifications, and RNA splicing are represented when referring to cellular proteins. “It is important to describe all the different forms of a protein that may exist in cells,” he explains.

    Recently, Dr. Smith and his colleagues collected proteomics and RNA-seq data from a homogeneous cell population, and developed a bioinformatics pipeline in which novel splice junction sequences were translated into the respective polypeptides, to establish a database that can be used to characterize splice junctions during mass spectrometry.

    “Using RNA-seq in conjunction with proteomics is more powerful than performing proteomics alone,” he says. While the strength of this analysis was illustrated in one cell type, efforts in Dr. Smith’s lab are currently directed toward characterizing splice junction peptides and splice site variation in additional cell types. “This is similar to giving glasses to proteomics, and its main advantage is the possibility to unveil splice variants that otherwise one could not see,” Dr. Smith adds.

    RNA-seq helped open new research avenues, forge inter- and cross-disciplinary connections, and define new concepts. Areas that historically received relatively little attention, such as RNA methylation, are now expanding into vibrant fields, while more recent disciplines, such as proteomics, are acquiring additional levels of inquiry.

    Knowing the extent to which learning about the genome reshaped our perspectives about biology, and considering the even more accentuated complexity of the transcriptome, one can only imagine the wealth and intricacy of the regulatory networks that are waiting to be elucidated.


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