CAREER: Algorithms for single molecule sequence analysis

职业：单分子序列分析算法

• 批准号: 1627442
• 负责人: Michael Schatz
• 金额: $ 119.69万
• 依托单位: Johns Hopkins University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-01-01 至 2022-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1627442&HistoricalAwards=false
• 关键词: CAREER; Algorithms; single; molecule; sequence

The Cold Spring Harbor Laboratory is awarded a CAREER grant for the PI Michael Schatz to develop new computational methods for processing DNA sequencing data from the latest high-throughput sequencing technologies. DNA sequencing costs and throughput have improved by orders of magnitudes over the last three decades, although many questions remain unsolved, especially because of the short sequence lengths currently available. Emerging "third generation" sequencing technology from Pacific Biosciences, Moleculo, Oxford Nanopore, and other companies are poised to revolutionize genomics by enabling the sequencing of long, individual molecules of DNA and RNA. The sequence lengths with these technologies can reach up to tens of thousands of nucleotides, however few or no analysis packages are capable of dealing with these types of genetic sequence data. This project will overcome these limitations by developing several novel analysis algorithms specifically for long read single molecule sequencing and their associated complex error models. The outcomes will help answer biological questions of profound significance to all of society, such as: What were the genetic implications of the domestication of rice? What genes and regulatory elements give rise to the incredible regenerative properties of the flatworm? or, What can be understood from assembling reference genomes of sugarcane and pineapple towards breeding more robust plant crops and biofuels?Specific objectives of the research include working towards assembling entire plant and animal chromosomes into complete, haplotype-phased sequences; identifying fusion genes and complex alternative splicing patterns responsible for diseases or adaptability; and searching for structural variations associated with improved crop yield or human diseases such as cancer or autism. Even if some future technology is capable of directly reading entire transcripts or entire genomes, this research will remain necessary to examine the higher level relationships across populations of genomes or in measuring the dynamics of gene expression and splicing.This project will tightly integrate research and education, promoting opportunities at high school through postdoctoral levels with the development of new course materials, hands-on research opportunities, and one-on-one mentoring experiences. This effort will specifically target the intersection of computer science and biology, promoting interdisciplinary education, and ensuring the next generation of scientists are ready for the complexities of quantitative and digital biology. To engage the widest possible audience, Dr Schatz will also develop novel online teaching materials made available through a yearly bioinformatics contest. The first round of the contest reached nearly 1000 students around the world and at all levels of education, engaging students far beyond our physical limits. The products of the research will be made available as open-source software, and installed into the graphical iPlant Discovery Environment making them easily accessible to the large community of plant researcher around the world.

冷泉港实验室被授予职业生涯补助金的PI迈克尔沙茨开发新的计算方法处理DNA测序数据从最新的高通量测序技术。在过去的三十年里，DNA测序的成本和通量已经提高了几个数量级，尽管许多问题仍然没有解决，特别是因为目前可用的短序列长度。来自Pacific Biosciences、Moleculo、Oxford Nanopore和其他公司的新兴“第三代”测序技术有望通过对长的单个DNA和RNA分子进行测序来彻底改变基因组学。这些技术的序列长度可以达到数万个核苷酸，但是很少或没有分析包能够处理这些类型的遗传序列数据。该项目将通过开发几种专门用于长读单分子测序及其相关复杂错误模型的新型分析算法来克服这些限制。这些结果将有助于回答对整个社会具有深远意义的生物学问题，例如：水稻驯化的遗传意义是什么？是什么样的基因和调控因素导致了扁形虫令人难以置信的再生特性？或者，从组装甘蔗和菠萝的参考基因组到培育更健壮的植物作物和生物燃料，可以理解什么？该研究的具体目标包括将整个植物和动物染色体组装成完整的单倍型序列;识别融合基因和负责疾病或适应性的复杂选择性剪接模式;以及寻找与提高作物产量或人类疾病（如癌症或自闭症）相关的结构变异。即使未来的技术能够直接阅读整个转录本或整个基因组，这项研究仍然是必要的，以检查更高层次的关系，在人口的基因组或测量动态的基因表达和剪接。该项目将紧密结合研究和教育，促进机会，在高中到博士后水平的发展新的课程材料，动手研究的机会，和一对一的指导经验。这项工作将专门针对计算机科学和生物学的交叉，促进跨学科教育，并确保下一代科学家为定量和数字生物学的复杂性做好准备。为了吸引尽可能广泛的受众，Schatz博士还将开发新的在线教学材料，通过每年的生物信息学竞赛提供。第一轮比赛吸引了来自世界各地的近1000名学生，他们来自各个教育层次，吸引的学生远远超过了我们的身体极限。该研究的产品将作为开源软件提供，并安装到图形化的iPlant Discovery Environment中，使世界各地的大型植物研究人员社区可以轻松访问。