We have previously reported the generation of a large, integrated dataset whereby we, and other groups, can examine the relationships between genetic diversity and gene expression in the human brain. This has most immediate impact for understanding gene variants identified in genome-wide association studies where most nominated polymorphisms cannot immediately be assigned a function, as most do not change protein coding sequences. Rather, many are associated with differences in gene expression. We and others have used our data to derive such expression quantitative trait loci (eQTL) and have found them to be very helpful in understanding the genetic basis of a number of neurological and psychiatric conditions. However, our current dataset was generated using microarrays, which is a probe-based technique for estimating gene expression levels. Some of the known limitations of microarrays include that probes have only a single sequence whereas in the human genome, many genes are variable. Also, genes are alternatively spliced and edited which are poorly represented on most arrays. To overcome this, we are currently replacing our microarray based dataset with RNA-Seq, a newer technique that directly sequences expressed genes as well as providing measures of alternate exon using (ie splicing). We first applied this technique, and associated analytical approaches, to the mouse brain where we found substantial changes in gene expression, splicing and editing during development. Ongoing work in the laboratory includes applying the same approach to mouse models of disease and to a large series of human brains whose DNA has also been sequenced.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Investigator-Initiated Intramural Research Projects (ZIA)
Project #
1ZIAAG000947-06
Application #
8736661
Study Section
Project Start
Project End
Budget Start
Budget End
Support Year
6
Fiscal Year
2013
Total Cost
$253,451
Indirect Cost
Name
National Institute on Aging
Department
Type
DUNS #
City
State
Country
Zip Code
Dillman, Allissa A; Cookson, Mark R; Galter, Dagmar (2016) ADAR2 affects mRNA coding sequence edits with only modest effects on gene expression or splicing in vivo. RNA Biol 13:15-24
Blauwendraat, Cornelis; Francescatto, Margherita; Gibbs, J Raphael et al. (2016) Comprehensive promoter level expression quantitative trait loci analysis of the human frontal lobe. Genome Med 8:65
(2015) Common genetic variants influence human subcortical brain structures. Nature 520:224-9
Nalls, Mike A; Saad, Mohamad; Noyce, Alastair J et al. (2014) Genetic comorbidities in Parkinson's disease. Hum Mol Genet 23:831-41
Dillman, Allissa A; Cookson, Mark R (2014) Transcriptomic changes in brain development. Int Rev Neurobiol 116:233-50
Ramasamy, Adaikalavan; Trabzuni, Daniah; Guelfi, Sebastian et al. (2014) Genetic variability in the regulation of gene expression in ten regions of the human brain. Nat Neurosci 17:1418-28
Johnson, Janel O; Pioro, Erik P; Boehringer, Ashley et al. (2014) Mutations in the Matrin 3 gene cause familial amyotrophic lateral sclerosis. Nat Neurosci 17:664-6
Ramasamy, Adaikalavan; Trabzuni, Daniah; Gibbs, J Raphael et al. (2013) Resolving the polymorphism-in-probe problem is critical for correct interpretation of expression QTL studies. Nucleic Acids Res 41:e88
Majounie, Elisa; Cross, William; Newsway, Victoria et al. (2013) Variation in tau isoform expression in different brain regions and disease states. Neurobiol Aging 34:1922.e7-1922.e12
Holton, Patrick; Ryten, Mina; Nalls, Michael et al. (2013) Initial assessment of the pathogenic mechanisms of the recently identified Alzheimer risk Loci. Ann Hum Genet 77:85-105

Showing the most recent 10 out of 23 publications