If you have human samples of responders to a drug (n=27) and non-responders to this drug (n=38)
And have enough money to perform whole genome sequencing with depth of 50x coverage for tumours and 30x coverage for normal samples, with 94% of the known genome being sequenced to at least 8× coverage
Would chose to do WES or WGS?
In any case, please can you tell me your reasons in term of advantages?
Sounds like a theoretical question not one that has practical implications? You would need to take into account your budget and the final goals. WES would incur additional costs for capture etc on experimental side, which WGS would not. If you did the same amount of sequencing you would sample coding regions much deeper in WES than WGS.
I have already WGS, I noticed people done the same project on the same cancer by WES so I am trying to explain why we are repeating such a project by taking any advantage of WGS over the WES into account. In the other way I am justifying why we are doing this project and I can not find a good reason
Hi,
Some of the things which I understand. If you are going to talk about mutations that are affecting protein-coding sequences then there is no advantage of WGS over WES. In any case, these are some of the things that could be done by WGS (and not standard WES) -
1) Fusion genes - Many a times the junction boundary lies within an intronic region and hence WES is mostly unable to catch this.
2) Promoter mutations - Genes like TERT have established functional consequences for mutations in promoters. This genomic region is of course not covered by WES
3) Mutations that could affect splicing - If the mutations is in the splice-acceptor/ donor site (which is in the exonic region) or a couple of bases further away in the intron, then this get picked up in WES. But if there is a potential splice-site affecting variant further away in the intron then WGS has power.
4) Mutations in UTRs - Note that some of the WES target capture libraries pull-down un-translated region sequences (UTRs) as well (like Agilent has Exonic+UTR capture kit). But in case UTRs were not part of the WES kit, then WGS could give you insight.
Having said all that, you should realize that to get any variant(s) from above scenarios published in a good peer-reviewed journal would require downstream datasets like gene expression levels/ staining of tissue-blocks.
There are more blue-sky stuff that you could do from WGS (like look at selection constraints in the exonic versus the intronic regions, gene-wise) but it depends if you have a prior hypothesis or if you are going to 'search' for 'new' stuff. In any case, if the disease in question has had prior genomic studies published already, you would have to come-up with 'validation datasets' for reviewers to take note.
Generally, as others have already stated, it's a trade-off between cost and the regions sequenced. Also, the enrichment process for WES can lead to non-uniform coverage which results in regions with very high or very low coverage. This may result in missed variant calls in regions with low coverage. WGS, however, does not have the enrichment process like WES allowing for more uniform coverage (related PNAS paper).
Without knowing what you wish to do with your new data, all I can say is that, with WGS, you may be able to discover variants that could have been missed.
It is called exome-seq or WES, not exam-seq. Exome if you are only interested in coding regions, WGS if you are interested in the rest of the genome as well.
Thank you. In the cancer I am working on, there is a published list of driver genes already on which I have focused my analysis; In this case, as cancer driver genes are mainly are in the coding regions, so basically I am not beneficial from WGS advantages here because I am focusing on these genes. Am I right?
The answer very much depends on the mechanism of action of your drug. If your drug is an ALK inhibitor, you absolutely need the ability to detect ALK fusions. WES is good at finding point mutations in coding sequence, but is terrible at finding fusion genes. In the case of ALK, you'd be looking at WGS, an ALK fusion assay, or a capture panel that includes the introns of ALK.
WGS gives you a much more extensive of the rearrangement landscape of your cancer. ~70% of driver mutations involve some sort of genomic rearrangement. A lot of these are detectable in WES (e.g. loss of function caused by a SNV and CN loss will be reported in WES as a homozygous SNV), but many of these aren't.
If you're not looking at SVs, then WGS is a waste of money.
Shameless plug: our GRIDSS/PURPLE/LINX pipeline gives the most comprehensive picture of the somatic genomic rearrangements landscape of any pipeline that I'm aware of. It has some really nice features including driver prediction and can even identifiy and classify complex multi-breakpoint driver fusions. See our preprints here and here for more details.
Sounds like a theoretical question not one that has practical implications? You would need to take into account your budget and the final goals. WES would incur additional costs for capture etc on experimental side, which WGS would not. If you did the same amount of sequencing you would sample coding regions much deeper in WES than WGS.
I have already WGS, I noticed people done the same project on the same cancer by WES so I am trying to explain why we are repeating such a project by taking any advantage of WGS over the WES into account. In the other way I am justifying why we are doing this project and I can not find a good reason
Hi, Some of the things which I understand. If you are going to talk about mutations that are affecting protein-coding sequences then there is no advantage of WGS over WES. In any case, these are some of the things that could be done by WGS (and not standard WES) - 1) Fusion genes - Many a times the junction boundary lies within an intronic region and hence WES is mostly unable to catch this. 2) Promoter mutations - Genes like TERT have established functional consequences for mutations in promoters. This genomic region is of course not covered by WES 3) Mutations that could affect splicing - If the mutations is in the splice-acceptor/ donor site (which is in the exonic region) or a couple of bases further away in the intron, then this get picked up in WES. But if there is a potential splice-site affecting variant further away in the intron then WGS has power. 4) Mutations in UTRs - Note that some of the WES target capture libraries pull-down un-translated region sequences (UTRs) as well (like Agilent has Exonic+UTR capture kit). But in case UTRs were not part of the WES kit, then WGS could give you insight.
Having said all that, you should realize that to get any variant(s) from above scenarios published in a good peer-reviewed journal would require downstream datasets like gene expression levels/ staining of tissue-blocks.
There are more blue-sky stuff that you could do from WGS (like look at selection constraints in the exonic versus the intronic regions, gene-wise) but it depends if you have a prior hypothesis or if you are going to 'search' for 'new' stuff. In any case, if the disease in question has had prior genomic studies published already, you would have to come-up with 'validation datasets' for reviewers to take note.
Thanks a lot! Could you share the article about your opinions?
Generally, as others have already stated, it's a trade-off between cost and the regions sequenced. Also, the enrichment process for WES can lead to non-uniform coverage which results in regions with very high or very low coverage. This may result in missed variant calls in regions with low coverage. WGS, however, does not have the enrichment process like WES allowing for more uniform coverage (related PNAS paper).
Without knowing what you wish to do with your new data, all I can say is that, with WGS, you may be able to discover variants that could have been missed.