We will create a transcriptional atlas of the developing human brain, including novel transcripts and regional expression patterns that can be followed up subsequently with histochemical mapping for cellular specificity. These data will be made available to the research community at-large via an easy-to-use, web-based informatics framework. To accomplish these goals, we will purify RNA and DNA from 3 male and 3 female post-mortem brains at the approximate ages of 25 weeks, 2 months, 1year, 2.5 years, 7 years, 13 -19 years and 20-30 years. For the 25 week brains, we will sample Dorsolateral Prefrontal Cortex (DLPFC), Orbital Frontal Cortex (OFC), Inferior Temporal Cortex (ITC) and Hippocampus (HIP). The rest of the time points will add Occipital Cortex (OC), cerebellum (CB) and striatum (STR), for a total of 276 brain samples. We will profile DNA from these 276 samples with 1 million SNPs (Human1MDuo array) and will determine methylation patterns with an Illumina Infinium array. RNA from these 276 samples will be used to determine regional expression pattern, identify novel genes and alternative transcripts using RNA-Seq. Each poly-A RNA sample will be sequenced with 45 million reads to provide detection at 1 copy/cell (15%). 30 million of these reads will be 72 bp X 2 paired-end and 15 million reads will be 150+125 bp paired-end to provide the maximal information on alternative splicing. We will also sequence small RNA molecules from each sample using 15 million 36 bp strand specific single-end reads. The RNA-Seq data will be analyzed with GenomeStudio (Illumina, Inc.), ERANGE3, NextGENe"""""""" (Softgenetics Inc.), TransSeq (USC) and novel programs we will develop, to identify novel genes and determine the levels of transcription, allelic expression and alternative splicing of all genes. We will then compare these measures of transcription across brain regions, developmental ages and gender. We will also perform RNA-Seq with 5,000 bp read lengths using a third generation DNA sequencer (G3), in collaboration with Life Technologies, Inc, to confirm or refine our alternative splicing models. An automated RNA-Seq analysis workflow that is portable to other laboratories will be developed and an easy-to-use, web-based informatics framework for communication of these data to other scientists will be designed and implemented.
Mental disorders are increasingly recognized as brain disorders that have their origins during development. While these developmental brain disorders occur in people at genetic risk, relatively little is known about how specific risk genes or gene variants affect brain development. We will determine the expression patterns of genes in particular brain regions at particular points in development. This information is essential for understanding how genetic variation affects normal and abnormal brain development, potentially giving rise to mental disorders.
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