5' end bias in RNA-seq

 http://seqanswers.com/forums/showthread.php?t=13902

The bias will affect estimates of absolute expression, but once you calculate a fold change for a gene by comparing several samples, it should cancel out.

This holds if the patterns are the same in all samples. If they are not, you might get better results when adjusting for it. This is at least what Hansen et al. claim in their follow-up paper, a preprint of which you can find here: http://www.bepress.com/jhubiostat/paper227/

 

Good to read : cover broad issue in RNA-seq

https://www.labome.com/method/RNA-seq.html

Currently, all commercially available RNA-seq platforms rely on reverse transcription and PCR amplification prior to sequencing and sequencing is therefore subject to the biases inherent to these procedures. First, annealing of random hexamer primers to fragmented RNA is not random, which results in depletion of reads at both 5’ and 3’ ends [3-6]  

  

Figure 2. Sequence logo showing observed and expected nucleotide distribution surrounding the 5’ fragmentation site. Similar biases are present at the 3’ end. Image: Roberts et al. [3] (image released under a Creative Commons Attribution License). 

 

 

Figure 3. Read coverage over genes is biased against 3’ and 5’ extremities. Fragmentation was done by either RNA hydrolysis or cDNA shearing, and distribution of reads plotted for small (< 1 kb; top), medium (1-8 kb; middle) and large (> 8 kb; bottom) transcripts. Image modified from Huang et al. [4]. 

 

This makes the identification of the true start and end of novel transcripts a challenge, as well as underestimating expression level of short genes. Second, PCR can introduce bias based on GC content and length due to non-linear amplification [7, 8]. A number of data analysis tools to correct these biases are available, although achieving varying degrees of success [6, 9, 10].