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in the news: Exome Sequencing in the clinic

2/4/2014

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(image adapted from Choi et al., PNAS 2009)

A work published recently in the New England Journal of Medicine (Yang et al. Clinical whole-exome sequencing for the diagnosis of mendelian disorders. NEJM 2013) presents a summary of the findings of the application of Whole-Exome-Sequencing (WES) in a clinical setting.

The data used:  Researchers and medical doctors at the Baylor College of Medicine followed the results of the application of WES in 250 consecutive cases in search for the cause of rare (or unidentified) genetic diseases. A total of 62 cases (~25%) were able to be diagnosed via this next-generation sequencing approach, a yield that is significantly higher than other conventional genetic tests (~15%).  

The analysis: Analysis involved application of standard pipelines (quality control, mapping on the reference genome, calling of variants, functional analysis of variants after filtering for known SNPs). The results provided significant insight in the cause of various disease (most of which were related to neurological disorders associated to mental retardation). It is important to notice that not only the diagnostic yield was increased with the application of WES, but that even previously unknown gene-disease relationships were revealed through this approach.  Moreover, the inquiry at a genome-wide scale led to the identification of incidental findings in almost half of the positive cases (30/62) something which would have not been possible through conventional methods. One particular case is quite representative of the potential of WES. 
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"For example, one patient (Patient 14 in Table S3 in the Supplementary Appendix) had whole-exomesequencing ordered at 26 months of age. He had previously been evaluated by means of chromosomal microarray analysis, DNA methylation, eight single-gene sequencing tests, mitochondrial genome sequencing by next-generation sequencing, respiratory-chain enzyme analysis, and multiple biochemical analyte studies. On the basis of the charges listed for these tests, we found that the cost of this patient’s previous genetic testing was three times as high as the current cost of whole-exome sequencing. This patient carried a mutation in SYNGAP1, which is associated with a newly recognized nonsyndromic mental retardation that may not have been identified by conventional genetic testing. He also had an incidental, medically actionable mutation in FBN1 that would have escaped detection without whole-exome sequencing."

Taking into account that as the cases analyzed with WES increase, we are bound to be able to associate more diseases with previously unidentified genetic causes, It becomes increasingly relevant to consider WES as the standard approach for genetic testing.

What's next:  More exomes, faster and cheaper becoming routine practice in the clinic.

Read more: On whole exome sequencing (WES) and its applications in medical genetics in this report of the Baylor College of Medicine.
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in the news: Beware of ChIPs bearing gifts

2/3/2014

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Two recent works, one  published in Plos One (Park et al. Widespread misinterpretable ChIPSeq bias in yeast) and one in PNAS (Teytelman et al.  Highly expressed loci are vulnerable to misleading ChIPlocalization of multiple unrelated proteins) 
point out a very important artifact of a very widely applied method, ChIPSeq.  Both papers that appeared almost simultaneously show that there is an inherent bias in all ChIP experiments to result in enriching regions belonging to highly-expressed genes regardless of the nature of the studied protein.

The data used: Both groups performed a series of experiments in yeast but their results may readily be extended to more complex genomes. Park et al. mostly focused on Tup1,  a well-studied transcriptional supressor, the binding of which they surprisingly found to coincide with highly-expressed genes under multiple conditions. Teytelman et al.  did the same starting from a family of repressors known as Sir proteins which they also saw to be consistently located in genes with high-expression. 

The analysis: The analysis was pretty straight-forward. ChIPSeq data from various platforms were analyzed with standard peak-calling algorithms, such as MACS2 and the discovered peaks were correlated with the expression of the closest or overlapping genes. In all cases, a positive correlation was observed even if the protein under study was not a transcriptional activator. Teytelman et al. were able to show that a positive corrrelation was even observed in the case of a GFP ChIP experiment, that is a "mock" experiment with a protein that does not bind the DNA under normal conditions. The authors, thus, reach the conclusion that the major source of bias is the process of cross-linking which is likely to occur preferentially in actively transcribed regions.   

What's next:  Both papers point out a very important aspect that has largely escaped the attention of a huge number of published works. At the same time both groups suggest the performance of extensive controls for every ChIPSeq experiment to be performed in the future. For instance, performing a "mock" ChIP with a non-DNA-binding protein such as GFP and subtracting the signal (as representative of hyper-chipability) would distinguish signal from noise. This is bound to work to a great extent but is probably not cost-worthy, while it will complicate the downstream analysis through the addition of one more condition. On the other hand, new approaches that do away with cross-linking may provide more effective solutions.

Read more: A work published this week in Nature Methods by the group of S. Henikoff describing a methodology for inquiring transcription factor binding in native (non cross-linked) chromatin (Kazinathan et al. High-resolution mapping of transcription factor binding sites on native chromatin). This is probably the next step in this sort of approaches as native chromatin does away with cross-linking which is the main source of highly-expressed gene bias.

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