Past Awardee

Algorithms and Tools for Mammalian Genome Reconstruction Analysis

Jian Ma

College: Engineering
Award year: 2009-2010

Data generated from numerous mammalian genome sequencing projects have provided a unique opportunity to use comparative genomics to computationally reconstruct the evolutionary history of our species and of other living species of placental mammals. The goal is to provide the trajectory of all the genetic changes leading to modern species, which may lead to novel biomedical discoveries. However, due to the diversity and complexity in modern mammalian genomes, computationally reconstructing the ancestral genome and the record of genetic changes leading to present day species is algorithmically extremely challenging. It is essential to combine all the complex evolutionary operations into a single, computationally tractable model. To capture the circumstances surrounding each of the major genetic shifts that occurred in the genomes, new and more efficient algorithms handling more complex scenarios need to be developed to solve the reconstruction problem at all different scales. Moreover, with the recent advancement in next-generation high-throughput sequencing technologies, an unprecedented amount of genomic data will become available soon. It is critical to make the software tools highly scalable to assist with making discoveries using huge amount of genomic data. The objectives of this project are to: (1) develop algorithms that handle complex evolutionary operations and develop software tools that can run on massive amount of genomic data; (2) reconstruct the ancestral mammalian genome and the evolutionary history on different branches; (3) use the reconstruction to study mammalian genome evolution. By taking advantage of the resources at NCSA that are not obtainable elsewhere, this project will create a set of novel software tools and make initial effort to build a foundational resource detailing the evolution of the mammalian genomes that can potentially be used by many other researchers to explore the genomes in an evolutionary context.