Structural variations (SVs) are the largest source of genetic variation, but remain poorly understood because of limited genomics technology. Single molecule long read sequencing from Pacific Biosciences and Oxford Nanopore has the potential to dramatically advance the field, although their high error rates challenge existing methods. Addressing this need, we introduce open-source methods for l...

BACKGROUND In the process of protein evolution, sequence variations within protein families can cause changes in protein structures and functions. However, structures tend to be more conserved than sequences and functions. This leads to an intriguing question: what is the evolutionary mechanism by which sequence variations produce structural changes? To investigate this question, we focused on ...

The evolution of diversity across the animal kingdom has been accompanied by tremendous gene loss and gain. While comparative genomics has been fruitful to characterize differences in gene content across highly diverged species, little is known about the microevolution of structural variations that cause these differences in the first place. In order to investigate the genomic impact of structu...

Ribulose 1,5-bisphosphate carboxylase/oxygenase (RuBisCO) is the key enzyme to assimilate CO(2) into the biosphere. The nonredundant structural data sets for three RuBisCO domain superfamilies, i.e. large subunit C-terminal domain (LSC), large subunit N-terminal domain (LSN) and small subunit domain (SS), were selected using QR factorization based on the structural alignment with QH as the simi...

With the increasing popularity of whole-genome shotgun sequencing (WGSS) via high-throughput sequencing technologies, it is becoming highly desirable to perform comparative studies involving multiple individuals (from a specific population, race, or a group sharing a particular phenotype). The conventional approach for a comparative genome variation study involves two key steps: (1) each paired...

Structural variations (SVs) in genomic DNA can have profound effects on the evolution of living organisms, on phenotypic variations and on disease processes. A critical step in discovering the full extent of structural variations is the development of tools to characterize these variations accurately in next generation sequencing data. Toward this goal, we developed a software pipeline named di...