CPHx: Edwin Cuppen, Hubrecht Inst. and Utrecht University – Are we looking at the right places for pathogenic human generic variation?

CPHx: Edwin Cuppen, Hubrecht Inst. and Utrecht University – Are we looking at the right places for pathogenic human generic variation?

Where are we looking, typically?  Genomes.  Thus, we search for variations across the genome.  We then end up sequencing the whole genome, but then lack the tools to sequencing.

Reduce work and costs by multiplexing.  Typically, we multiplex sample prep, multiplex enrichment, then barcode.  Instead, multiplex enrichment would be more cost effective.

Barcode Blocking would be the way to go.

Example shown comparing to agilent sureSelct – exactly the same.  Have pushed so far to 5 samples in this case.

You can also show this scales to 96x-fold, however, then you need proportionally more sequencing for large data sets. (eg, wouldn’t want to do this for a genome.)

Average base coverage per sample using 96-plex.  It is between 40-100x, so there’s only a 2-fold distribution.

Do you see allelic competition in enrichment pool? It’s possible, but in practice, you don’t see it.

Example given for X-exome screenome.  Only one enrichment with all of the different families, so it’s more cost effective.  Show ability to identify causative variants.

Are we looking at the right places?  UTRs, promoters, enhancers, insulators, chromatin organizers, non-coding RNA.  There is much more than just protein coding sections in the genome.  However, if we look at the whole genome, there are limitations there too.  And still, what about structural variations?

Mate Pair sequencing of structural variation using mate-pair sequencing.  Not only do you get distance of structural variations, you also get direction information.

Proof of principle.  Detection of a three way translocation.  Started with a diagnosed patient.  It was found by standard cytogenetic analysis, but the question was if they could find it using structural variant detection. Sequenced father, mother, child.

Thousands of predicted structural events.  It includes errors in reference, it includes artefacts.  Some are just found in mother or father – inherited.  Are you finding the known breakpoints?  Yes… but they found more.  It was not just 3, it was far more.

10 of them were then confirmed, including the three that were expected.  Original data set did not make predictions about disrupted genes.  Looking at the new breakpoints observed, however, one was a protocadherin15, which is mutated in Usher syndrome – which explains the phenotype.

Cytogenetics gives you less information, which is simple, but the next gen sequencing gives you way more information, and can then give explanatory power.  In fact, you can use den novo to make sense of the data more effectively and reconstruct the chromosomes.  You can even get single bp resolution.

Chromothripsis.  Shattering and reassembling of chromosomes.  Some pieces are lost, others are mixed, and reassembly occurs giving you information that would be challenging to identify otherwise.  Were able to reconstruct this data.

Mate pair seq in diagnostics.  Tag-density and mate-pair information can be used. Trio based approach used.  They were able to identify exact gene disrupted, where other approaches failed.  Single bp resolution.

You can also use it to resolve complex rearagements that could not otherwise be visualized with other technique.  Chromothripsis may be much more common than expected, as it has been observed in other samples.

Can be applied to cancer research.  Tumour specific structural variation.  There is significant differences between two tumours of the same type, even.

Chromothripsis looked for in cancer samples.. expected 2-4%.  Found it in all but one sample.  (looking in metastatic colorectal cancer.)  Chromotripsis seems to be a common phenomonon driving cancer events.

Able to find expected events as well, and able to find known cancer genes affected by the arrangements.

Also went back to exome sequencing.  Found a few interesting mutations in known cancer genes.

Conclusions.

Multiplexed targetd sequencing aproaches are effective for large and small sample sets.

Structural variation can be relevant and is largely missed, but can be assayed by using mate pair sequencing.

Chromothripsis is a novel and frequent process that contribututes to dramatic somatic and germline structural variation and disease.

For understanding disease, we need to evaluate genomes at the nucleotide AND the structural level.

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