A few months ago, I discussed a paper by Li and colleagues reporting a large number of sequence differences between mRNA and DNA from the same individual [1]. While some such differences are expected due to known mechanisms of RNA editing (e.g. A->I editing, see [2]), Li et al. reported an astonishingly high number of them, including thousands of events inconsistent with any known regulatory mechanism. These results implied at least one, and probably many, new mechanisms of gene regulation, and called into question some basic assumptions in molecular biology.
An alternative explanation for the observations of Li et al. is less exciting–imagine two genes with similar (but not identical) sequences, which produce similar (but not identical) mRNAs. If you accidentally attributed both mRNA sequences to the same gene, you could erroneously conclude that one of the two sequences arose via RNA editing of the other. According to a new paper in by Schrider and colleagues [3], this banal artifact accounts for the majority of the reported RNA-DNA sequence differences in Li et al.
Schrider et al. show that RNA-DNA mismatches are enriched in genes with close paralogs or copy number variants, both of which are consistent with the technical artifact mentioned above. However, their most striking result is that, at many of the putative RNA editing sites, the “edited” base from the mRNA is actually present in genomic DNA. To show this, Schrider et al. took advantage of the fact that low-coverage DNA sequencing data is available for the individuals used in the Li et al. study. They searched through these data to find genomic sequences matching the “edited” mRNA form. If these sites were truly due to RNA editing, they shouldn’t find any. Instead, at ~75% of the tested sites, they could find a genomic match to the “edit” in at least one individual. There are some potential complications with the interpretation of this number (as they note, the genomic data could include sequencing errors that happen to be the same base as the “edit”), but this observation strongly suggests that a majority of the sites identified by Li et al. are false positives due to this single technical issue.
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[1] Li et al. (2011) Widespread RNA and DNA Sequence Differences in the Human Transcriptome. Science. doi: 10.1126/science.1207018
[2] Levanon et al. (2004) Systematic identification of abundant A-to-I editing sites in the human transcriptome. Nature Biotechnology. doi:10.1038/nbt996
[3] Schrider et al. (2011) Very Few RNA and DNA Sequence Differences in the Human Transcriptome. PLoS One. doi:10.1371/journal.pone.0025842








In PLoS Genetics this week there is a
Genome-wide association studies have been hugely successful in identifying dozens of common genetic risk factors for a large number of common diseases. However, one area that GWAS has not had much success in is the field of psychiatric illness, where finding common risk factors that replicate across studies has been consistently difficult. However, it looks like this is starting to change. The current issue of Nature Genetics has two papers from the Psychiatric GWAS Consortium, detailing some of the largest meta-analyses of 


This week sees the
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