Does single base resolution in sequencing means that very base could be accurately identified? So that the SNP could be genotyped by this sequencing technology? If this true, I think this conception would only be suitable for DNA and DNA related sequencing. Why there are so many RNA-seq method claim that they were single base resolution, like GRO-seq and eCLIP-seq?
Hi jinyu ,
In a single sentence, the answer to your question can be summarized as, "the resolution of a genomic technology refers to the smallest genomic variant that can be assayed by the technology". For Single-base, then, it refers to a technology that can distinguish the presence and absence of SNVs reliably.
Part of the reason there are so many genomic technologies is the desire to cheaply assay classes of variation that affect nucleotide sequences over 9 orders of magnitude in size. Consider - a whole genome duplication event is of interest as an early step in carcinogenesis - thats on the order of 10^9. NGS tech is virtually blind to pure WGD events - but a much much older technology, karyotyping, can assay it easily. At 10^0, we have the SNV, which you allude to in the original post. Every OoM between those has scientifically and medically relevant questions that depend on it, too.
Nowadays since people are used to conceptualizing technologies that sequence every base the term can require clarification - its true. But we just need to remember that not all technologies work by giving information on individual DNA (or RNA) bases. However, this was untrue for ~1/2 the history of genomics.
An intriguing comment that you've made has to do with a perceived division between utility of single base resolution in DNA vs. in RNA. If I understand correctly, I think I'd frame it differently - that it has less to do with nucleotide vs. nucleoside and everything to do with the scale of analysis that is of interest to the experimenter.
The phenomenon of RNA-editing has led to issues with accurate sequencing of RNA, for example, in routine RNA-seq studies. For better or for worse, much of the RNA data generated was used to do things like differential expression analysis. By contrast, the number of attempts to report and/or directly analyzing primary sequence of RNA is comparatively small (to clarify, I am saying the data are analyzed at the level of belonging to a gene or transcript, rather than analyzed at an individual base level). But here again the issue is the desired resolution of the analysis, not what is possible/impossible with RNA. Its certainly possible and useful to do it, it just requires more care to get it right.
Great comprehensive explanation and overview of the technologies -- with regards to sequencing assays, the one thing I'd add is SNV identification is only one mode of "single base" resolution profiling; the other context is RT drop-off (if it consistently happens at a specific site, we can call that specific site that it occurs at).
Thank you for your detail and great explanation. I do need more time to understand these. And there is still something compuzzling me. For instance, why WGS sequencing could be used to call SNV but this a rare thing for common total RNA-seq? You known, 90% + genomic region is transcripted. So, total RNA-seq theoretically covers most genome region. And why ATAC-seq and ChIP-seq could be used to analyse allele imbalanced open chromatin signal or histone modification? But there were nearly no study to do this analysis using RNA-seq for allele imbalanced gene expression.
You known, 90% + genomic region is transcripted. So, total RNA-seq theoretically covers most genome region.
Perhaps but not all of that is happening at the same time. You are also unlikely to capture every transcribed fragment in your libraries.
See this answer for some considerations for/against using RNAseq for SNP discovery: Inferring genotype based on RNA sequences (RNA-seq variant calling)
I think that term means slightly different things in different contexts. For example, it's useful to profile mRNA modifications (e.g. m6a) -- this is obviously at "single base" resolution. Or, I guess in the case of, say, RNA binding protein experiments (finding RNA-protein covalent crosslinked sites), "single base" resolution is distinguished from "transcript" resolution (you know a protein binds a particular transcript, just not where along the transcript) or 100 bp resolution (you don't get the exact binding motif -- you might get a 100 bp sequence but where the protein actually binds within those 100 bps can't really be determined). For example, in those CLIP-like assays, if RT terminates at a cross-linked nucleotide and you identify what/where that particular nucleotide is, you have "single base" resolution.
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Sequencing by hybridization (https://en.wikipedia.org/wiki/Sequencing_by_hybridization ) is likely not giving you single base resolution. But sequencing by synthesis (most current sequencing technologies with exception of Nanopore) should offer single base resolution.
GROseq and eCLIP-seq are techniques that are used for mapping binding sites for RNA pol-II and RBP. But the final sequencing of the cDNA is done using seq by synthesis.