Transcriptional Atlas of Human Brain Development

描述(申请人提供)：我们将创建一份人类大脑发育过程的转录图谱，包括新的转录本和区域表达模式，随后可以通过组织化学图谱进行细胞特异性研究。这些数据将通过一个易于使用的、基于网络的信息学框架向广大研究界提供。为了实现这些目标，我们将从大约25周、2个月、1岁、2.5岁、7岁、13-19岁和20-30岁的死后脑中提取3名男性和3名女性的RNA和DNA。对于25周的大脑，我们将取样背外侧前额叶皮质(DLPFC)、眶前叶皮质(OFC)、颞叶下皮质(ITC)和海马区(HIP)。其余的时间点将增加枕叶皮质(OC)、小脑(CB)和纹状体(STR)，总共276个大脑样本。我们将用100万个SNP(Human1MDuo阵列)从这276个样本中提取DNA，并用Illumina Infinium阵列确定甲基化模式。这276个样本的RNA将用于确定区域表达模式，识别新基因和使用RNA-Seq的替代转录本。每个Poly-A RNA样本将通过4500万次读取进行测序，以提供1拷贝/细胞(15%)的检测。其中3000万个读数将是72bpX2成对端，1500万个读数将是150+125bp成对端，以提供有关替代剪接的最大信息。我们还将使用1500万个36bp链的特定单端读数对每个样本中的小RNA分子进行测序。RNA-Seq数据将用GenomeStudio(Illumina，Inc.)、ERANGE3、NextGENe“(SoftGenetics Inc.)、TransSeq(USC)和我们将开发的新程序进行分析，以识别新基因，并确定所有基因的转录水平、等位基因表达和选择性剪接。然后，我们将比较不同大脑区域、发育年龄和性别的转录指标。我们还将与Life Technologies，Inc.合作，使用第三代DNA测序仪(G3)进行5,000 bp读取长度的RNA-Seq，以确认或改进我们的替代剪接模型。将开发一个可移植到其他实验室的自动RNA-Seq分析工作流程，并将设计和实施一个易于使用的、基于网络的信息学框架，以便将这些数据传达给其他科学家。 公共卫生相关性：精神障碍越来越多地被认为是起源于发育期间的大脑疾病。虽然这些发育性大脑疾病发生在有遗传风险的人身上，但人们对特定的风险基因或基因变异如何影响大脑发育知之甚少。我们将确定基因在发育特定时间点的特定大脑区域的表达模式。这些信息对于理解基因变异如何影响正常和异常的大脑发育，潜在地导致精神障碍是至关重要的。

DESCRIPTION (provided by applicant): 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. PUBLIC HEALTH RELEVANCE: 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.