III: EAGER: Novel algorithms for de novo transcriptome assembly using RNA-seq data and for metagenome assembly

III：EAGER：使用 RNA-seq 数据从头转录组组装和宏基因组组装的新算法

• 批准号: 1553680
• 负责人: Xiuzhen Huang
• 金额: $ 9.93万
• 依托单位: Arkansas State University Main Campus
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1553680&HistoricalAwards=false
• 关键词: III; EAGER; Novel; algorithms; de

While high-throughput sequencing technology provides an unprecedented opportunity to reveal the complexity of transcriptomes or metagenomes, it poses a significant challenge to accurately and efficiently assemble the huge amount of short fragments into transcriptomes or genomes. A number of assemblers have been developed, but they all have limitations that have hindered their applications. This project will develop novel approaches, which would transform the method design and development of the challenging transcriptome and metagenome assembly. This project will also help educate students through seminars and courses how effective computational models could make a difference in addressing bioinformatics challenges.Based on the new insights gained through the preliminary work on a heuristic approach-based de novo assembler Bridger, recently published in Genome Biology, this project will develop novel algorithms for de novo transcriptome assembly using RNA-seq data. The novelty of the approach lies in (1) new graph models, different from the de Bruijn graph or overlap graph of existing assemblers, and (2) the search algorithms, both of which will integrate sequence coverage depth information and paired-end reads into the procedure. It is anticipated that the new approach will achieve significantly increased sensitivity and specificity, compared with current de novo assemblers including Trinity or even current reference-based assemblers such as Cufflinks or StringTie. Furthermore, based on the algorithmic techniques developed for transcriptome assembly and the common features between transcriptome and metagenome assemblies, this project will explore and develop algorithms to assemble metagenomes, which is a computationally demanding task due to the mixture of large collections of short DNA sequence fragments from many different organisms, and the inconsistency of sequencing coverage of different organisms. For further information see the project web site at: http://bioinformatics.astate.edu/assembly/

虽然高通量测序技术为揭示转录组或宏基因组的复杂性提供了前所未有的机会，但准确有效地将大量短片段组装成转录组或基因组却构成了重大挑战。已经开发了许多汇编器，但它们都有限制，阻碍了它们的应用。该项目将开发新的方法，这将改变具有挑战性的转录组和宏基因组组装的方法设计和开发。该项目还将通过研讨会和课程帮助学生了解有效的计算模型如何在应对生物信息学挑战方面发挥作用。基于最近发表在《基因组生物学》上的基于启发式方法的从头组装程序布里杰的初步工作所获得的新见解，该项目将开发使用RNA-seq数据的从头转录组组装的新算法。该方法的新奇在于（1）新的图模型，不同于现有组装器的de Bruijn图或重叠图，以及（2）搜索算法，这两者都将序列覆盖深度信息和配对末端读取整合到程序中。预计与当前的从头组装器（包括Trinity）或甚至当前基于参考的组装器（如Cufflinks或StringTie）相比，新方法将实现显著增加的灵敏度和特异性。此外，基于为转录组组装开发的算法技术以及转录组和宏基因组组装之间的共同特征，本项目将探索和开发组装宏基因组的算法，由于来自许多不同生物体的大量短DNA序列片段的混合，以及不同生物体的测序覆盖范围的不一致性，这是一项计算要求很高的任务。欲了解更多信息，请访问项目网站：http://bioinformatics.astate.edu/assembly/