Mitochondrial Genomics

Now is the age of very large molecular data in systematics. However, our ability to analyze large and complex molecular data is severely outpaced by our ability to generate such data. My research aims at bridging this gap in the context of mitochondrial genomics. Mitochondrial genomes (mtgenomes) are the smallest extant organellar genome, which in insects encode for 13 protein-coding, 22 tRNA and 2 rRNA genes with an average size about 15,000 bp. It is now technically feasible to sequence the mtgenome of a given organism in its entirety within a short period of time. The complexity of the genome structure and the large yet manageable size of the genome make mitochondrial genomics an ideal model system for exploring various challenges of today’s molecular systematics.

As a postdoctoral research fellow of an NSF-funded AToL Beetle Tree of Life Project, I generated complete mtgenome sequences for 72 key beetle species and I am conducting a similar research on Orthoptera as well. I was involved in developing a bioinformatics tool that can aid genome annotation and data management [MOSAS].

The availability of mtgenomes from diverse lineages within a given taxonomic group allowed me to study genome evolution in a comparative context. My research has focused on the evolution of genome structures, atypical stop codons, transfer RNAs, and lineage-specific gene rearrangements in a phylogenetic framework. I am also interested in determining how best to analyze mtgenome data as a phylogenetic marker for deep-level relationships. So far, I have shown that mtgenome data are often highly affected by the past molecular events, resulting in patterns such as among-site rate variation and base compositional heterogeneity and that incorrect phylogenetic inference is inevitable when such systematic bias is not accounted for. I am currently exploring various ways to overcome systematic bias in phylogenetic reconstruction.

Representative Papers:

  • Leavitt, J.R.*, Hiatt, K.D.*, Whiting, M.F., and Song, H. 2013. Searching for the optimal data partitioning strategy in mitochondrial phylogenomics: A phylogeny of Acridoidea (Insecta: Orthoptera: Caelifera) as a case study. Molecular Phylogenetics and Evolution 67: 494-508.
  • Sheffield, N.C.*, Hiatt, K.D.*, Valentine, M.C., Song, H., and Whiting, M.F. 2010. Mitochondrial genomics in Orthoptera using MOSAS. Mitochondrial DNA 21(3-4): 87-104.
  • Song, H., Sheffield, N.C.*, Cameron, S.L., Miller, K.B. and Whiting, M.F. 2010 When phylogenetic assumptions are violated: The effect of base compositional heterogeneity and among-site rate variation in beetle mitochondrial phylogenomics. Systematic Entomology 35(3): 429-448.