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 这类重要变异的基础生物学。因此，体细胞变异目录 由SMaHT网络生产的产品满足了基本需求。为了建立这个目录，新的方法和 由于目前的方法不能全面评估体细胞结构， 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 计算方法的基础上长读测序，并将使该方法广泛使用 在SmaHT网络上。这些方法将利用新的算法和机器学习 这种方法是可扩展的，并且以较低的成本提供降低的错误率。会有一个特别的焦点 关于识别转座子在基因组中的运动。为此，我们将实施 更好地注释和表征插入和易位， 换位此外，我们将从长读序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在体内表达。 改变塑造了关键区域的甲基化模式，并可能影响基因。培养 与其他小组合作，我们将与SMaHT测序和分析密切合作 中心.多种活动，如NIST和SMaHT体细胞变异基准的形成， 以及年度黑客松，将吸引来自世界各地的调查人员。该集团的历史 成功的方法开发将确保SMaHT网络将获得有用的， 全面的新工具，以扩大体细胞和镶嵌SV和转座的知识。