Mapping human brain cell type-specific isoform usage in ASD

自闭症谱系障碍（ASD）等精神疾病影响着数百万人及其家庭 国际吧遗传风险在ASD的病因学中起着重要的作用，我们已经表明，大脑的变化 mRNA在异构体水平的表达，而不是基因表达的整体变化，显示出最大的影响 大小和基因富集。然而，大脑中同种型多样性的程度及其在大脑中的失调， 像ASD这样的疾病，由于许多亚型不能在细胞类型水平上分辨， 通过常用的短读RNAseq技术，尚未直接分析。因此，迫切需要 需要评估亚型表达的作用及其与ASD相关遗传变异的关系-精确 细胞类型和空间特异性，以了解它赋予疾病的神经生物学机制 风险我们的目标是解决这些和其他缺陷，在我们的理解景观的异构体表达 在典型的神经和患病的大脑中。因此，我们将使用长读段RNA同种型测序来产生同种型 绘制并表征3个脑区全长同种型的结构、表达丰度和用途 与自闭症有关我们将通过深入分析50个高置信度ASD风险基因来进一步补充， 同种型失调的证据，以鉴定细胞水平上的同种型表达模式。 在目标1中，我们将对尸检组织进行全转录组全长（FL）RNA亚型测序（IsoSeq）。 海马（HC）和纹状体（STR）脑组织的ASD病例和神经典型对照，并结合联合收割机， 数据与我们现有的数据前额叶皮层（PFC）构建一个全面的地图异构体表达 大脑的三个区域。值得注意的是，我们还将使用我们的正常和失调全长的参考图谱， 同种型表达作为分析来自ASD病例的> 2，000个RNAseq数据集的概要的先验， PsychENCODE联盟和其他努力积累的控制，并确定失调的亚型， 同种型共表达网络模块。在目标2中，我们将使用一种补充方法来分析单核 ASD和对照组中相同PFC、HC和STR组织的表达差异，以消除 使用10 X snIsoSeqCap在细胞类型水平上检测50个ASD风险基因，这是一种对FL-1进行测序的新方法。 在单个核/细胞水平上，所选基因的整个长度上的转录物。我们将进行整合 分析以鉴定组织和细胞类型之间的同种型表达差异，以及选定的同种型变化 将通过RNA荧光原位杂交（FISH）和定量亚型特异性PCR在选定的 神经元和非神经元细胞类型。 这里生成的图谱将改进现有的参考基因组注释，并允许解决主要的 关于人脑中同种型表达的悬而未决的问题。新的数据和方法将 为神经科学界提供了巨大的资源，为更好地了解神经生物学铺平了道路。 ASD的遗传风险机制。

Psychiatric disorders such as autism spectrum disorder (ASD) affect millions of individuals and their families worldwide. Genetic risk plays an important role in the etiology of ASD, and we have shown that changes in brain mRNA expression at the isoform-level, rather than overall changes in gene expression, show the largest effect sizes and genetic enrichments. However, the extent of isoform diversity in brain, and its dysregulation in disorders such as ASD, is vastly underexplored because many isoforms cannot be resolved at the cell type-level by commonly used short-read RNAseq technologies and are yet to be directly profiled. Thus, there is an urgent need to assess the role of isoform expression and its relation to ASD-associated genetic variation − with precise cell-type and spatial specificity to understand the neurobiological mechanisms through which it confers disease risk. Our goal is to address these and other deficits in our understanding of the landscape of isoform expression in neurotypical and diseased brain. As such, we will use long-read RNA isoform sequencing to generate isoform maps and characterize the structure, expression abundance and usage of full-length isoforms in 3 brain regions implicated in ASD. We will further complement by deeply profiling 50 high-confidence ASD risk genes with evidence of isoform dysregulation, to identify isoform expression patterns at the cellular level. In Aim 1 we will perform whole-transcriptome full-length (FL) RNA isoform sequencing (IsoSeq) of postmortem hippocampus (HC) and striatum (STR) brain tissues of ASD cases and neurotypical controls, and combine the data with our existing data for prefrontal cortex (PFC) to construct a comprehensive map of isoform expression across the 3 brain regions. Notably, we will also use our reference maps of normal and dysregulated full-length isoform expression as priors for analyses of a compendium of >2,000 RNAseq datasets from ASD cases and controls amassed by the PsychENCODE consortium and other efforts, and identify dysregulated isoforms and isoform co-expression network modules. In Aim 2 we will use a complementary approach to profile single-nuclei of the same PFC, HC and STR tissues in ASD and controls to disambiguate isoform expression differences of 50 ASD risk genes at the cell-type level using 10X snIsoSeqCap, which is a novel assay to sequence FL- transcripts of selected genes across their entire length at the single nucleus/cell level. We will perform integrative analyses to identify isoform expression differences between tissues and cell types, and selected isoform changes will be validated by RNA fluorescent in situ hybridization (FISH) and quantitative isoform-specific PCR in selected neuronal and non-neuronal cell types. The maps generated here will improve existing reference genome annotations, and allow to address major outstanding questions regarding isoform expression in human brain. The new data and methodologies will provide a tremendous resource for the neuroscience community, paving the way to better inform neurobiological mechanisms of genetic risk for ASD.