Identification of somatic/ mosaic SV and transposon activity and their crosstalk to DNA epigenetic Modifications

体细胞/嵌合 SV 和转座子活性的鉴定及其与 DNA 表观遗传修饰的串扰

• 批准号: 10662143
• 负责人: Fritz J Sedlazeck
• 金额: $ 29.48万
• 依托单位: BAYLOR COLLEGE OF MEDICINE
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-04-15 至 2025-03-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10662143
• 关键词: Address; Algorithms; Attention; Awareness; Belief; Benchmarking; Biology; Blood; Brain; Catalogs; Collaborations; Communities; Complex; Computer software; Computing Methodologies; DNA; DNA Sequence; DNA Sequence Alteration; DNA Transposable Elements; Data; Detection; Disease; Elements; Ensure; Epigenetic Process; Ethnic Origin; Evaluation; Event; Feedback; Fostering; Frequencies; Gene Expression; Genes; Genome; Genomic Segment; Human; Human Genome; Individual; Knowledge; Laboratories; Liver; Location; Machine Learning; Malignant Neoplasms; Measures; Methodology; Methods; Methylation; Modification; Mosaicism; Movement; Mutation; Phase; Population; Production; Recording of previous events; Research Personnel; Resolution; Shapes; Short Tandem Repeat; Signal Transduction; Single Nucleotide Polymorphism; Somatic Mutation; Statistical Models; Tandem Repeat Sequences; Technology; Tissues; Variant; Work; analytical method; cost; genetic variant; hackathon; human reference genome; improved; insight; method development; methylation pattern; mosaic; mosaic variant; novel; tool; variant detection

Studies of somatic mutation have so far focused on cancer or other severe diseases, with little attention to the basic biology of this important class of variation. As a consequence, the somatic variation catalog to be produced by the SMaHT network fills an essential need. To build this catalog, novel methods and approaches are required since current methods cannot comprehensively assess somatic structural variation (SV) nor transposon activation at scale, or with adequate resolution. We will develop novel computational methods based on long-read sequencing and will make the methods broadly available across the SMaHT network. The approaches will leverage new algorithmic and machine learning approaches, be scalable and provide a reduced error rate, at lower cost. There will be a special focus on the identification of the movement of transposons across the genome. For this we will implement better annotation and characterization of insertions and translocations that are evidence for transposition. In addition, we will identify methylation signals from long-read sequencing data. Correlation of methylation changes and somatic & mosaic mutations will reveal how these genomic alterations shape the methylation patterns in critical regions and likely impact genes. To foster the collaboration with other groups we will closely work together with SMaHT sequencing and analysis centers. Multiple activities such as the formation of a NIST & SMaHT somatic variation benchmarks, as well as annual Hackathons, will engage investigators from around the world. The group’s history of successful methods development will ensure that the SMaHT network will receive useful and comprehensive new tools to extend the knowledge of somatic and mosaic SVs and transposition.

迄今为止，体细胞突变的研究主要集中在癌症或其他严重疾病上，很少受到关注 体细胞变异目录是这一重要变异类别的基础生物学。 由 SMaHT 网络制作满足了构建此目录的基本需求，新颖的方法和方法。 由于目前的方法无法全面评估体细胞结构，因此需要采取一些方法 大规模变异（SV）或转座子激活，或具有足够的分辨率，我们将开发新的。 基于长读长测序的计算方法将使这些方法广泛可用 这些方法将利用新的算法和机器学习。 方法，可扩展并以较低的成本提供较低的错误率将是一个特别的重点。 为此，我们将实施识别转座子在基因组中的运动。 更好地注释和描述插入和易位，作为证据 此外，我们还将从长读测序数据中识别甲基化信号。 甲基化变化与体细胞和嵌合突变的相关性将揭示这些基因组如何 改变塑造关键区域的甲基化模式并可能影响基因。 与其他小组合作我们将与 SMaHT 测序和分析密切合作 多项活动，例如 NIST 和 SMaHT 体细胞变异基准的形成， 以及一年一度的黑客马拉松，将吸引来自世界各地的研究人员参与该组织的历史。 成功的方法开发将确保 SMaHT 网络将获得有用且 全面的新工具可扩展体细胞和嵌合 SV 和转座的知识。