New Year – new papers. The United Nations has declared 2014 the International Year of Family Farming and Crystallography.
But for epilepsy genetics it will be the year of genotyping and sequencing. Hopefully, these studies will translate into with major insights in epilepsy genetics.
In the last years pioneer studies have presented first analysis methods for genome data in a disease context. Several data quality control and statistical methods are now well established and more and more data is available for application. This week’s studies point out the importance of thinking outside the box as well as data dissecting from a different perspective.
Ohnologs and CNVs. Is a specific class of genes overrepresented in large recurrent pathogenic CNVs? Using an evolutionary genetic approach, McLysaght and colleagues demonstrate that ohnologs are overrepresented in pathogenic CNVs in their recent PNAS study. Ohnologs are genes retained after ancestral whole-genome duplication events. McLysaght and colleagues suggest that ohnologs represent critical dosage-sensitive elements of the genome and are possibly responsible for some of the deleterious phenotypes observed for pathogenic CNVs. In the field of epilepsy genetics, we usually identify a huge amount of truncating mutations in an individual patient exome in addition to CNVs. Are ohnologs also enriched for truncating mutations in patients?
A life with Rasmussen encephalitis. Research scientists like me don’t see patients and therefore are not involved on a personal level in the same way that clinicians are. In genomics we work with patient data every day, knowing that disease associated variants are hidden somewhere in the data cloud. Analyzing the data in depth does not only need motivation but also true dedication. To get motivated for this, read the personal story of Seth Wohlberg, who writes about his life with Rasmussen encephalitis in his family. This video on mutation identification in a family with cerebral palsy is also a must watch for genome scientists as well as clinicians skeptical towards genomics.
Gut-microbiome-brain connection in neurodevelopmental disorders. Behavior and metabolism are connected – after all, the way to a man’s heart is through his stomach. But the emerging correlation of gut microbe composition and autism is something new. In a current paper in Cell, Hsiao and coworkers demonstrate that alterations in gut permeability and microbial composition forces autism-like behavior in mice. The phenotype could be rescued by treating mice with specific nutrients. More research on gut-brain metabolism is warranted in epilepsy research. Maybe the ketogenic diet as a treatment in GLUT1 deficiency syndrome is just the beginning.
Somatic mutation distribution in cancer genomes. In the last years, it has been shown that somatic mutations play a key role in the development of cancer. However, distinguishing between deleterious mutations and genomic noise is not easy, in parallel to interpreting de novo mutations in epileptic encephalopathies. In the latest edition of Nature Biotechnology, Polak and colleagues link fine-scale chromatin accessibility to cancer mutation accumulation. They demonstrate that mutations are highly reduced in accessible regulatory DNA defined by DNase I hypersensitive sites. These results may help define a baseline for cancer genomics projects targeting noncoding regions.
MicroRNAs and possible implications for idiopathic disease. Do you know enough about microRNAs in context of disease? In a recent issue of Frontiers Molecular Neuroscience, Forstner and coworkers review the latest research on MicroRNAs in the etiology of schizophrenia. They specifically investigate studies on genes affected by the 22q11.2 deletion. This deletion is a strong risk factor for schizophrenia. We and others have also detected this deletion in patients with epilepsy. Therefore, understanding the pathogenic effects of miR-185 is also of interest for epilepsy research.
Combined association and in silico prediction analysis of KCNJ10 SNPs in patients with IGE from India. You are interested in computational analysis of potential deleterious non-synonymous SNPs? In a recent article in Gene, Phani and colleagues investigate the association of several coding SNPs in KCNJ10 and epilepsy as a phenotype. They use a variety of tools in parallel to narrow down potential disease-causing SNPs. The methods section of the study provides a good overview of tools currently used for in silico functional prediction of mutations.
I hope you enjoyed the first edition of papers of the week in 2014. I wish you a good start in to the New Year.