The overall goal of the following experiment is to be able to identify de novo mutations in common genetic disorders. Once a disease that corresponds with the de novo mutation hypothesis has been identified, critical criteria are applied for the selection of patient cases from which to scan for de novo mutations. Next, high quality, low throughput sequencing, or whole exome sequencing is used to identify such mutations using this strategy.
De Novo mutations in the Shank three gene were found in subjects affected with schizophrenia. Though this method can provide insights into the genetics of schizophrenia and autism. It can also be used to study other common diseases such as Melo retardation.
Not all diseases fit the de Novo Disease profile. So before outlining the protocol, these are the essential criteria a disease must meet to be a candidate to Novo mutation disease. Diseased patients show a reduction in fitness.
The disease is found frequently in widely variable environments. The disease is sometimes associated with a higher paternal age. Classic linkage and association studies fail to explain a significant fraction of disease heritability.
And lastly, twin concordance data must support a de novo model. Next, apply criteria to select samples with a high likelihood of possessing a de novo mutation. De novo mutation correlates with early onset, severe phenotypes, unaffected parents and older fathers that lack disease symptoms.
The availability of DNA can limit sample selection. Unless samples are available from both the patient and the patient's parents, transmittance cannot be ruled out. Additionally, the availability of additional affected cohorts and normal subjects are also needed for validation of an identified candidate gene.
When a sufficiently large sample size of candidates and controls are collected, proceed with the analysis selection of the best candidate. Genes is based on a scoring system. For example, this set of criteria can be used for scoring genes associated with neurocognitive diseases.
Neurological diseases like a myotrophic lateral sclerosis, for example, would use very different criteria. They include synaptic implication evidence, synaptic localization, evidence, tissue expression, pattern data, animal model, cognition, data, arguments from genetic analysis and involvement. After applying these criteria, many genes can be parsed out of the study in favor of better candidates.
After sequencing, the candidate genes apply a combination of two or more sequence analysis tools, because they usually work differently. For example, the false positive mutation rate for SMPs as calculated by polys scan software as shown in this graph, is higher than what is calculated by poly Fred software. Polys scan also shows a lower mutation rate for indels than poly Fred.
As a final step for each novel, exonic variant eliminate technical artifacts by reifying, by PCR and resequencing. The region of interest from DNA extracted from blood samples from the patient, and both parents performing this step on blood DNA is important as some mutations may be due to artifacts caused by the division of cultured lymphoblasts cell lines. A powerful alternative to sequencing selected candidate genes is to use high throughput sequencing to sequence the coding regions of 16, 000 genes.
Kits are now available to prepare samples for whole exome sequencing from various commercial companies. When these sequences are returned to the lab, there are several bioinformatics tools for detection and genotyping genomic variation to choose from. Now before prioritizing mutations within the whole exome, select variants from ranked candidate genes as explained earlier.
For all variants, each should be prioritized according to two criteria. First, the variant should be unique and neither present in the parents, nor in public s and p databases. Second, the variants are predicted to affect the gene's function according to their location in the sequence by either truncating or altering.
The coating. Programs like PolyPhen, sift and Panther can all make these predictions to identify other causative mutations and ascertain that the identified mutations are not present in healthy individuals resequence the entire gene in additional patient cases and in controls. Any gene containing at least one de novo mutation predicted to be deleterious should receive further validation Studies confirmed variants can be functionally characterized by performing mRNA and or protein analysis on cell lines or animal models carrying the mutations.
These functional analyses could be done on cell lines or animal models using the high quality low throughput canida gene approach. A gene with two different de novo mutations was found in schizophrenia patients. One nonsense mutation was found in three affected brothers.
In this family, the mutation resulted in a premature termination signal at code on 1, 117 of the gene shank.Three. In a different family, a missense mutation in the same gene was found in an affected female. This mutation changes in arginine to tryptophan, a very different amino acid at Codon 536.
So after watching this video and using the methods described, you should be able to evaluate your disease of interest to see whether or not the Novo mutations play a role.
