An interesting historical breakdown of gene identification for rare skeletal diseases in the 25 years from 1988 to 2011.
What becomes apparent is that technology clearly drives the process of gene discovery and that there are ‘peaks in discovery’ that are closely aligned with ‘new’ technologies.
The availability of highly informative microsatelllite markers, which could even be assembled into panels for multiplexing (pioneered by Jim Weber in Marshfield Wisconsin), heralded the first increase in gene identification starting in the early to mid 1990’s.
This approach was massively enhanced with the publication of the Human Genome, which allowed a rapid transition from candidate region to candidate genes. For example, in our multiple epiphyseal dysplasia (MED) study of 2001 we went from a linked candidate region of 60cM to three candidate genes; TIMP3, SDC1 and MATN3 – we chose wisely Chapman et al 01.
High throughput SNP analysis aided in the identification of numerous genes responsible for recessive skeletal diseases through homozygosity mapping.
Most recently arrays and next generation sequencing has completely revolutionised disease gene discovery in rare (skeletal) diseases.
A super example of gene discovery using exome sequencing comes from Andreas Zankl, Matt Brown and colleagues.
In summary, exome sequencing of both parents and the affected siblings in this family identified:-
90% of targeted nucleotides had coverage of >four-fold
79% of targeted nucleotides had coverage >ten-fold
~15,000 SNPs identified following bioinformatic filtering!
>96% SNPs were reported in the recent dbSNP database and were therefore excluded from further analysis as unlikely to cause this rare disease.
Following the functional annotation of the remaining novel SNPs, focused analyses on a set of 483 unique novel coding non-synonymous SNPs that were detected in at least one sample.
Careful selection of ‘mode of inheritance’ allowed the identification of just four candidate genes.
In all but one gene the detected missense mutations were predicted to be tolerated in terms of effect upon protein function.
The single remaining candidate gene carried two novel alleles :-
One creating a premature stop codon.
One causing a missense mutation predicted to have a damaging effect on protein function.
POP1 a strong candidate for the disease-causing gene in this family.
Needless to say that this story made a great 2nd year undergraduate lecture Exome Lecture.
……..the start of the English first class cricket season!
M.C.C. v Durham at Abu Dhabi – I know the first game is not being played in England this year, but have you seen the weather forecast for tomorrow !
Over 125 years of history and tradition
Okay, so picture on the left shows the great Australian batsman Victor Trumper, but he was a ‘great’ of the golden age of cricket (1890-1914) and the picture of him ‘jumping out to drive” taken by Bedlam at the Oval in 1902 is a classic. Another classical batsman is Ian Bell of Warwickshire and England.
Global Genes Partners With SWAN USA To Help Undiagnosed Rare Disease Patients Seek A Medical Diagnosis Through Free Whole Exome Sequencing Program
The Global Genes Project, a non-profit rare disease advocacy organisation and Syndromes Without A Name USA (SWAN USA), another non-profit support organisation for patients with undiagnosed syndromes, are funding an initiative to provide 30 patients free whole exome sequencing.
Is there a need for ‘next generation diagnostics’ for rare skeletal diseases?
Yes of course there is; this is a large group of clinically variable and genetically heterogeneous diseases, moreover, many of the candidate genes are very large and have numerous exons.
The Greenwood Genetic Center has recently developed and employed a “NGS Skeletal Dysplasia Panel”. The 10 genes included on the panel account for more than 30 distinct clinical phenotypes. They have previously suggested that an estimated 90% of individuals with a skeletal dysplasia have a mutation in one of these ten genes. Whilst this number is likely to be optimistic, and indeed their own study suggest 45% of patients is a more accurate figure, it non-the-less suggests a good clinical utility for next generation diagnostics for rare skeletal diseases.
The first mutations in COMP were identified in 1995 in patients with both PSACH and MED and subsequently there has been over 30 publications describing COMP mutations in at least 250 PSACH–MED patients.
However, despite these discoveries, a methodical analysis of the relationship between COMP mutations and phenotypes has not been undertaken. In particular, there has, to date, been little correlation between the type and location of a COMP mutation and the resulting phenotype of PSACH or MED.
To determine if genotype to phenotype correlations could be derived for COMP, we collated 300 COMP mutations, including 25 recently identified novel mutations. The results of this analysis demonstrate that mutations in specific residues and/or regions of the type III repeats of COMP are significantly associated with either PSACH or MED.
This newly derived genotype to phenotype correlation may aid in determining the prognosis of PSACH and MED, including the prediction of disease severity, and in the long term guide genetic counselling and contribute to the clinical management of patients with these diseases.