Should I remove PCR duplicates from my RNA-seq data?

Should I remove PCR duplicates from my RNA-seq data?

The short and generalized answer to the question “Should I remove PCR duplicates from my RNA-seq data?” is in most cases NO.  For some scenarios, de-duplification can be helpful, but only when using UMIs. Please see the details below.

The vast majority of RNA-seq data are analyzed without duplicate removal. Duplicate removal is not possible for single-read data (without UMIs). De-duplification is more likely to cause harm to the analysis than to provide benefits even for paired-end data (Parekh et al.  2016; below).  This is because the use of simple sequence comparisons or the typical use of alignment coordinates to identify “duplicated reads” will lead to the removal of valid biological duplicates.  RNA-seq library preparation involves several processing steps (e.g. fragmentation, random priming, A-tailing, ligation); none of these processes is truly random or unbiased.  Thus, the occurrence of “duplicated reads” in between millions of reads can be expected even in paired-end read data. Short transcripts and very highly expressed transcripts will show the majority of such “natural” duplicates. Their removal would distort the data.  For example plant RNA-seq data often seem to contain large amounts of duplicated reads. This is in part due to the fact the gene expression in many plant tissues, like leaves, is dominated by a small number of transcripts; much more so than in most animal samples. Another concern is that the fraction of reads identified as “duplicated” is correlated to the number of aligned reads. Thus, one would have to normalize any data set for equal read numbers to avoid introducing additional bias.

Several studies (among them Parekh et al.  2016; below) have shown that retaining PCR- and Illumina clustering duplicates does not cause significant artifacts as long as the library complexity is sufficient.  The library complexity is in most cases directly related to the amount of starting material available for the library preparation. Chemical inhibitors present in the sample could also cause low conversion efficiency and thus reduced library complexities.
PCR duplicates are thus mostly a problem for very low input or for extremely deep RNA -sequencing projects.  In these cases, UMIs (Unique Molecular Identifiers) should be used to prevent the removal of natural duplicates.   UMIs are for example standard in almost all single-cell RNA-seq protocols.

The usage of UMIs is recommended primarily for two scenarios: very low input samples and very deep sequencing of RNA-seq libraries (> 80 million reads per sample). UMIs are also employed for the detection of ultra-low frequency mutations in DNA sequencing (e.g. Duplex-Seq).  For other types of projects, UMIs will have a minor effect in reducing PCR amplification induced technical noise.
Our 3′-Tag-RNA-Seq protocol employs UMIs by default. For other RNA-seq applications please request UMIs on the submission form. When using UMIs for conventional RNA-seq, genomic DNA-sequencing, or ChIOP-seq, the first eleven bases of both forward and reverse reads will represent UMI and linker sequences. These are then followed by the biological insert sequences. The UMI sequences are usually trimmed off and the information transferred into the read ID header with software utilities like UMI-Tools.

Please see the discussion here for details:
https://www.biostars.org/p/55648/   and these excellent papers
Parekh et al 2016:  The impact of amplification on differential expression analyses by RNA-seq.  and
Fu et al. 2018:  Elimination of PCR duplicates in RNA-seq and small RNA-seq using unique molecular identifiers.
Kennedy et al 2015: Detecting ultralow-frequency mutations by Duplex Sequencing. 

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This blog post “molecularecologist.com/2016/08/the-trouble-with-pcr-duplicates”  offers a detailed analysis of the effect of increasing read numbers on the frequency of PCR duplicates as well as the occurrence of false-positive duplicate identifications on another type of Illumina sequencing data (RAD-seq). Please note that the library type studied is different from RNA-seq as are the potential effects of PCR duplicates for this type of analysis. In contrast to RNA-seq, PCR duplicates should be removed for most RAD-seq studies.


Category: 06 Sequencing Data

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