Yes, this amazing technology is not just a tool for basic researcher anymore, but has made its way in to the clinical routine testing. It currently all about exome sequencing and targeted gene panel analysis, but whole genome sequencing is expected to come into clinical routine soon. Have a read through this comprehensive article which describes very nicely which applications are suitable for the diagnostic testing and which may come in the future.
Selective characterisation of the genome’s complete coding region
In humans, only 1-2 % of the genome is protein coding, the so-called exome. Exome sequencing is favoured over whole genome sequencing due to costs, efficiency and the easier interpretability of a much lower data volume compared to whole genome sequencing. It gains more and more clinical relevance in the determination of rare diseases as well as for cancer research and diagnostics. Furthermore, it’s a very important screening tool for genetic variations e. g. involved in mental disorders such as schizophrenia and is therefore increasingly used as one genomic application in drug discovery. Exome analyses are frequently conducted as trio analyses with one patient plus healthy parents, who serve as controls to filter out benign variants. They are not only performed on behalf of companies or academic research organisations, but also gain more importance in diagnostic applications for individuals.
The most common technologies for exome analysis are based on in-solution hybridisation. They use a protocol that first generates a whole genome library, and then enriches the exome portion of the genome. The well-established kits for this kind of analysis are from NimbleGen, Agilent and Illumina. The exome enriched DNA is then primarily sequenced with Next Generation Sequencing systems from Ilumina, like Illumina HiSeq. This approach is typically selected for projects with large sample numbers. One limitation is the incomplete coverage for some genetic loci. More consistent sequence coverage can be achieved by using a PCR based exome capture approach offered by Ion Torrent. This approach allows a very fast and a more uniform exome analysis ideal for small to mid-size sample numbers.
Over the last years, exome sequencing has become a standard application. Every day, huge amounts of data are generated which need to be interpreted. However: Are we sure that our analysis is always showing us the complete picture?
Based on experience, coverage can significantly vary over the entire exome. For this reason, not only the average on-target coverage should be considered, but also the local coverage at a particular site of interest. Otherwise, important information may get lost.
Researchers of the University of Edinburgh and the Wellcome Trust Sanger Institute have carried out a study which was recently published in BMC Bioinformatics. They analysed how sequencing depth relates to sensitivity of SNV detection. They used a set of 30 captured exomes, which had been sequenced to a high depth. As basis for the analyses, they selected a set of verified “gold standard” SNVs for each sample. Then they generated different randomly selected subsets of each data set. In the next step, they called SNVs on the full data sets and the downsampled sets.
From those studies, they estimated that in order to detect at least 95% of the heterozygous SNVs, the local coverage at a given site of interest must be at least 13-fold, while a 3-fold coverage would be sufficient to detect a homozygous SNV. On the other hand, an average on-target coverage of 20fold would result in 5-15% of the heterozygous and 1-4% of the homozygous SNVs to be missed.
They concluded that one does not necessarily have to go for excessively high coverage for exome sequencing, but one should consider how likely a polymorphism could remain undetected.
Actually, the same considerations should be made when looking at whole genome data.
The group has developed software to help researchers check their data. It can be applied to determine the local and overall SNV detection sensitivity of a given data set. The software is available for free download.
What is your experience? Share your expert knowledge with us!
Here is a short introduction of our new colleagues from AROS:
- AROS was founded in the year 2000
- AROS started as a spin off of from the Aarhus University Hospital and was the first service provider for Affymetrix in Europe
- AROS is based in Denmark and provides a long term experience in sample preparation, microarray analysis and next generation sequencing (NGS)
- Nowadays AROS has a leading position in NGS service for pharmaceutical research
- AROS is an Illumina reference lab for next generation sequencing
- The main focus in NGS is RNA-Seq and exome sequencing that is accomplished with the exome designs of the leading provider in this area (Illumina TruSeq Exome Enrichment, NimbleGen EZ Capture & Agilent SureSelect)
“AROS is an excellent fit […] with our focus on high-quality next-generation sequencing […]” (Dr. Gilles Martin) and therefore I am confident that this new alliance will help us both in further expanding our experience level in NGS and to benefit from our complementary strength.
I am sure you will hear more about the activities from AROS on our blog and hope you join me in welcoming AROS as a member of Eurofins.
Dear Blog readers,
today I am really delighted to announce the launch of the NGS Favourites.
NGS Favourites are the straightforward solution for your Next Generation Sequencing project. They are based on the wealth of knowledge that we have accumulated from over 5 years of servicing the NGS community and represent optimised packages for common NGS applications.
The NGS Favourites stand out due to:
- Project-oriented solutions
- Economic costs
- Easy ordering
The NGS Favourites are available for different fields of applications:
- Genome Sequencing Favourites – using shotgun (SG) libraries only or a combination of SG and LPE libraries
- Transcriptome Sequencing Favourites – receive comprehensive data you can really build on
- Exome Sequencing Favourites – sequence 6 human Exomes with the Illumina TruSeq Kit
- Library Service Favourites – get your libraries for GS FLX sequencing prepared from us
Find your suitable Favourite and explore the easy way of sequencing with us as your professional project partner.
Many large scale exome sequencing projects are funded and underway to analyze rare Mendelian diseases. This technology is often the choice as it is more affordable than whole genome sequencing (WGS) and therefore allows analyzing more patients. In addition it has the advantage that resulting data volumes are much smaller and therefore easier to handle.
But – when looking only on those regions targeted by the exome technology – are the results of an exome sequencing experiment really comparable to a WGS experiment?
The study from Clark et al., 2011 focused on this question and found that neither of the technologies managed to cover all sequencing variants. When applying 50 million reads for exome sequencing and 35-fold coverage for WGS, the study came to the following results.
– WGS detected between 660 and 4600 SNPs that were not called from the exome sequencing data and
– Exome Sequencing detected between 2600 and 3200 SNPs that were not called from the WGS data.
What can we conclude from this? First, WGS can not and will not replace exome sequencing as due to genome characteristics there will always be regions that are not covered sufficiently for SNP calling. As oligonucleotide designs of available exomes are balanced regarding regions with low coverage, exome sequencing shows higher sensitivity towards these regions. Second, WGS has its value in detecting variants in regions that are not covered by exome enrichment technologies. These are regions where enrichment fails as well as regions that are not present on the current exome designs.
So for covering really all variants it might be worth thinking about doing both experiments in parallel. Both technologies complement each other.
The June webinar of the free NimbleGen webinar series is talking about
Genome-wide studies of copy number variation and exome sequencing identify rare variants in BAG3 as a cause of dilated cardiomyopathy >
For further information and registration, please visit the NimbleGen website.