The broad impact of environmental exposures on repetitive element expression in cellular biology

环境暴露对细胞生物学中重复元件表达的广泛影响

• 批准号: 9143518
• 负责人: Richard Woychik
• 金额: $ 57.46万
• 依托单位: NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/9143518
• 关键词: Actins; Address; Alleles; Amino Acids; Animals; Antithymoglobulin; Appearance; Area; Behavior; Bioinformatics; Biological; Brain; Cells; Cellular Morphology; Cellular biology; Chimeric Proteins; Chromosomal translocation; Chromosomes; Cocaine; Cocaine Dependence; Code; Color; Complementary DNA; Computer software; Coupled; Cues; Cytokinesis; Cytoskeleton; DNA; DNA Methylation; Data; Data Set; Development; Diabetes Mellitus; Diet; Dinucleoside Phosphates; Ectopic Expression; Elements; Embryo; Environment; Environmental Exposure; Epigenetic Process; Evaluation; Event; Exons; Exposure to; Gene Expression; Gene Expression Regulation; Gene Fusion; Genes; Genetic Transcription; Genome; Genomics; Goals; Guanine Nucleotide Exchange Factors; Histones; Injection of therapeutic agent; Introns; Learning; Link; Malignant Neoplasms; Maps; Metabolism; MicroRNAs; Mitochondria; Modification; Mus; Mutagens; Mutation; N-terminal; Obesity; Organism; Outcome; Oxygen; Penetrance; Phenotype; Post-Translational Protein Processing; Production; Protein Isoforms; Proteins; Protocols documentation; Publishing; Quantitative Trait Loci; RNA Splicing; Reading; Recruitment Activity; Relative (related person); Repetitive Sequence; Research; Research Personnel; Reverse Transcription; Rewards; Saline; Series; Site; Spliced Genes; Staging; Tail; Testing; Time; Tissues; Transcript; Translations; Untranslated RNA; Variant; Virus; Work; base; cell type; cocaine exposure; design; drug of abuse; environmental agent; epigenetic regulation; fusion gene; genome-wide; insight; interest; male; migration; novel strategies; preference; research study; response; rho; transcriptome sequencing; vector

The purpose of this project is to better understand how repetitive elements (REs) may potentially impact the biological outcome of environmental exposures. While it is known that the expression of REs change in response to environmental agents, mechanistic insights into the impact of REs on the biology of cells and organisms is an area of research that has not been explored in depth. We are specifically interested in studying the extent to which REs alter the expression of adjacent genes through the formation of fusion transcripts (FTs). We chose to use RNAseq to study this problem. We developed a robust bioinformatics pipeline to detect FTs and have been analyzing a data set associated with cocaine exposure, which was selected based on the fact that our collaborator, Dr Eric Nestler, previously demonstrated that the expression of REs is altered in the brains of mice treated with cocaine. Also, we reasoned that the identification of FTs that are responsive to cocaine could provide a link between FTs and environmental exposures. The pipeline to detect FTs utilized the software package TopHat-Fusion, which was created to identify FTs originating from chromosomal translocations in cancer. We incorporated a series of stringent criteria for detecting FTs that involved: (i) each end of the fusion read had to be mapped to one genomic locus, (ii) one end of the fusion read had to be mapped to a repeat locus and the other end had to map to an annotated exon, (iii) the junction site of the fusion had to be flanked by canonical splicing dinucleotides, and (iv) the predicted fusion event had to be detected in all independent replicates from either experimental group. In this study the experimental groups were composed of a total of 15 saline- or 15 cocaine-exposed animals, representing 3 independent replicates with 5 animals each. Using this approach we identified 466 genes that express FTs, 165 of which were modulated by cocaine exposure. About 25 independent FTs were validated using reverse-transcription PCR, and from these we selected 9 for a more in-depth analysis. We first compared the level of FT expression relative to a non-fusion isoform of the same gene using quantitative real-time PCR (qRT-PCR). This revealed that, depending upon the gene, FTs were expressed at levels that were either higher, the same, or lower than the corresponding non-fusion isoform. These 9 genes expressing FTs were also analyzed for tissue-specific as well as developmental stage-specific expression. We found that expression of FTs is tightly regulated, with some being expressed in a tissue and/or developmenttal-specific manner, and, in some cases, that differ significantly from their non-fusion counterparts. We also focused on some genes that expressed FTs were responsive to cocaine. One such gene that expressed two different FTs, Arhgef10, is a rho guanine nucleotide exchange factor. This gene ultimately regulates the actin cytoskeleton in a way that can influence cellular morphology, migration, and cytokinesis. The first FT, fusion A, involves an LTR of an Endogenous Retroviral element (ERV) located 18Kb upstream from the canonical TSS of the gene that splices to the first coding exon of the gene with the annotated ATG. The second FT, fusion B, involves a LTR of an ERV located within the second intron that splices to the third exon of the gene, which is downstream from the annotated ATG. While we predict that the fusion A transcript would give rise to a normal protein, fusion B would need to recruit a downstream ATG in order to initiate translation. The first downstream ATG is located in exon 6, which would encode an N-terminal truncated protein that is 221 amino acids shorter than the normal protein. Interestingly, previously published results form other investigators demonstrated that the N-terminus of Arhgef10 encodes a negative regulatory domain, deletion of which gives rise to a hyperactive protein. Also we found that that Arhgef10 is present within one of the few quantitative trait loci (QTL) associated with cocaine addiction. These data, coupled with our finding that the fusion B transcript was upregulated 40% upon cocaine exposure, led us to test whether this fusion gene has the capacity to influence cocaine responsive behaviors. For this purpose we prepared virus vectors expressing GFP, wild-type or the fusion B cDNAs from Arhgef10. Virus prepared from these vectors was stereotaxically injected into the brains of 22 male animals. Two days following injections mice were divided into saline- or cocaine-treated groups (N=11/group) and subjected to the conditioned placement preference protocol where animals learn to prefer a cocaine-paired environment. We found that expression of the Arhgef10 fusion B transcript significantly decreased the time animals spent in the cocaine-conditioned chamber when compared to either the wild-type or GFP controls. This result indicated that the ectopic expression specifically of the fusion B transcript blunts the reward response to cocaine. Taken together, our data clearly indicate that FTs are abundantly formed in the NAc, can be regulated in spatial- and temporal-specific manner, and can respond to an environmental cue like cocaine. We are currently analyzing other publicly available and our own RNAseq data sets (including the ones of our mitochondrial manipulations as described in Project 1) to better understand which genes have the capacity to express FTs and to establish the full biological impact of FT expression. In the past year we have also started working with our collaborator Dr Riadi in the development of a new bioinformatics pipeline to more comprehensively identify FTs across the genome. For instance, the new pipeline is being designed to address the analysis of repeats that map to more than one genomic locus, and the identification of FTs that are read through events (only events that require splicing are currently detected). This new approach relies largely on statistical analysis of genomic-wide distributions of repeats and annotated genes, which is an initial step to allow the identification of the landscape of all potential fusion events across the genome. Preliminary analyses based on DNA configurations have indicated that the range of distances between a repeat and an exon involved in a fusion based on our TopHat-Fusion analysis is 1-360Kb which is significantly different than the average distance of the nearest repeat to any intron/exon on the genome.

该项目的目的是更好地了解重复元素（RE）可能如何影响环境暴露的生物学结果。 虽然众所周知，RE 的表达会随着环境因素的变化而变化，但有关 RE 对细胞和生物体生物学影响的机制见解是一个尚未深入探索的研究领域。我们特别感兴趣的是研究 RE 通过形成融合转录本 (FT) 改变邻近基因表达的程度。我们选择使用RNAseq来研究这个问题。 我们开发了一个强大的生物信息学流程来检测 FT，并一直在分析与可卡因暴露相关的数据集，选择该数据集是基于我们的合作者 Eric Nestler 博士之前证明，接受可卡因治疗的小鼠大脑中 RE 的表达发生了改变。此外，我们推断，识别对可卡因有反应的 FT 可以提供 FT 与环境暴露之间的联系。 检测 FT 的流程利用了软件包 TopHat-Fusion，该软件包的创建是为了识别源自癌症染色体易位的 FT。我们纳入了一系列严格的 FT 检测标准，其中包括：(i) 融合读段的每一端必须映射到一个基因组基因座，(ii) 融合读段的一端必须映射到重复基因座，另一端必须映射到带注释的外显子，(iii) 融合的连接位点必须侧翼为规范剪接二核苷酸，以及 (iv) 预测的 必须在任一实验组的所有独立重复中检测到融合事件。在这项研究中，实验组由总共 15 只暴露于盐水或 15 只暴露于可卡因的动物组成，代表 3 个独立的重复，每个重复 5 只动物。使用这种方法，我们鉴定了 466 个表达 FT 的基因，其中 165 个基因受到可卡因暴露的调节。使用逆转录 PCR 验证了大约 25 个独立的 FT，我们从中选择了 9 个进行更深入的分析。我们首先使用定量实时 PCR (qRT-PCR) 比较了相对于同一基因的非融合亚型的 FT 表达水平。这表明，根据基因的不同，FT 的表达水平可能高于、相同或低于相应的非融合亚型。 还分析了这 9 个表达 FT 的基因的组织特异性以及发育阶段特异性表达。我们发现 FT 的表达受到严格调控，其中一些以组织和/或发育特异性方式表达，并且在某些情况下，与非融合对应物显着不同。 我们还关注了一些表达 FT 对可卡因有反应的基因。 Arhgef10 是一种表达两种不同 FT 的基因，它是一种 rho 鸟嘌呤核苷酸交换因子。 该基因最终以影响细胞形态、迁移和胞质分裂的方式调节肌动蛋白细胞骨架。 第一个 FT，融合 A，涉及位于基因规范 TSS 上游 18Kb 处的内源逆转录病毒元件 (ERV) 的 LTR，该元件与带有注释的 ATG 的基因的第一个编码外显子剪接。第二个 FT，融合 B，涉及位于第二个内含子内的 ERV 的 LTR，该内含子剪接至基因的第三个外显子，该外显子位于注释的 ATG 下游。虽然我们预测融合 A 转录物会产生正常蛋白质，但融合 B 需要招募下游 ATG 才能启动翻译。第一个下游 ATG 位于外显子 6，它将编码 N 端截短的蛋白质，比正常蛋白质短 221 个氨基酸。 有趣的是，其他研究人员之前发表的结果表明，Arhgef10 的 N 末端编码一个负调节结构域，删除该结构域会产生一种过度活跃的蛋白质。我们还发现 Arhgef10 存在于与可卡因成瘾相关的少数数量性状基因座 (QTL) 之一中。这些数据，加上我们发现接触可卡因后融合 B 转录本上调 40%，使我们能够测试该融合基因是否具有影响可卡因反应行为的能力。为此，我们制备了表达 GFP、野生型或来自 Arhgef10 的融合 B cDNA 的病毒载体。 由这些载体制备的病毒被立体定位注射到 22 只雄性动物的大脑中。注射两天后，将小鼠分为生理盐水或可卡因治疗组（N=11/组），并接受条件放置偏好方案，其中动物学会更喜欢可卡因配对的环境。我们发现，与野生型或 GFP 对照相比，Arhgef10 融合 B 转录本的表达显着减少了动物在可卡因条件室中度过的时间。 该结果表明融合B转录物的异位表达特异性减弱了对可卡因的奖赏反应。 总而言之，我们的数据清楚地表明 FT 在 NAc 中大量形成，可以以空间和时间特定的方式进行调节，并且可以对可卡因等环境线索做出反应。我们目前正在分析其他公开可用的和我们自己的 RNAseq 数据集（包括项目 1 中描述的线粒体操作数据集），以更好地了解哪些基因具有表达 FT 的能力，并确定 FT 表达的完整生物学影响。 去年，我们还开始与合作者 Riadi 博士合作开发新的生物信息学流程，以更全面地识别整个基因组中的 FT。 例如，新的流程旨在解决映射到多个基因组位点的重复的分析，以及通过事件读取的 FT 的识别（当前仅检测需要剪接的事件）。 这种新方法很大程度上依赖于对重复和注释基因的全基因组分布的统计分析，这是识别整个基因组中所有潜在融合事件的第一步。 基于 DNA 配置的初步分析表明，根据我们的 TopHat-Fusion 分析，参与融合的重复序列和外显子之间的距离范围为 1-360Kb，这与基因组上任何内含子/外显子最近重复序列的平均距离显着不同。