Non-uniform illumina coverage, why?

Question

[bitjunkie]

Hello everyone, I have some new Illumina datasets that show non-uniform coverage (last image). My older datasets have uniform coverage across the whole genome (first image).

I don't know what library method was used for the first image, but for the second I am pretty sure it was the nextera kit. I extracted the gDNA with a phenol/chloroform procedure. I did not do the library prep but I will in the future.

What is the mostly likely reason for non-uniform coverage? How can I avoid this in the future?

Do you think the results warrant another sequencing run if I'm trying to identify mutations? A total of 3KB, in stretches of 10s to a few hundred bases, has zero coverage. The genome is AT-rich and about 4 Mb long. My guess is that this dataset if fine.

Images were generated with breseq.

Answer 1

[Brian Bushnell]

Was this MDA-amplified? Or, what kind of amplification was done, if any? You get the most even coverage when using unamplified isolates with an adequate amount of DNA.

Answer 2

[Kevin Blighe]

I have seen worse than this, and, in my case, it was due to the fact that many of my target regions exhibited high sequence similarity to other regions of the genome. Thus, reads that should have gone to my target regions were being 'robbed' by other regions of similar sequence. This, coupled with other target regions that had relatively 'unique' sequence, results in a distorted coverage profile much more exaggerated than the profile you've posted.

It isn't necessarily a problem and I would say that your data is fine. However, set a high mapping quality in order to ensure that your reads have high probability of mapping to the regions that you expect the to.