Since its inception in 2012, Dfam has demonstrated the promise of using profile hidden Markov Models (HMMs) to improve the detection sensitivity and annotation quality of Transposable Element (TEs) families in human and subsequently for four additional reference organisms. Despite these advances, the tools used to discover new families ( de-novo repeat finders ), improve families ( extend, defragment, subfamily clustering ), and classify TE families continue to depend on consensus sequence models. This discordance between methodologies is a direct impediment to Dfam’s expansion.
Daniel Olson has been named as a 2017 CBSD Summer Graduate Fellow. Each year, the University of Montana’s Center for Biomolecular and Structural Dynamics supports a small number of graduate students for a summer of research. Daniel, will enter the grad program here in the fall but has already begun research on models for repetitive biological sequences. That he was granted a fellowship for the summer prior to his first year in a grad program is a testimony to the excellent contributions he has already made to research on this campus, beginning with Art Woods and continuing in the Wheeler lab. Congratulations, Daniel!
Congratulations to Joyce Liu, a Sentinel High student who has been working with the Wheeler lab for the past couple years. She was recently awarded 2nd place in the Montana Tech Regional Science and Engineering Fair (link), for her project Investigating the Role of Pseudogenes as the Source of Conserved Non-Coding Elements in the Human Genome.
The Wheeler lab has been awarded an NIH R15 grant from the National Institute of General Medical Sciences to develop “Improved protein-DNA models for translated sequence search with profile Hidden Markov models”. The grant is for $426K over three years, beginning April 1, 2017.
Fast and sensitive sequence database search is fundamental to modern molecular biology. The funded research will improve the accuracy of annotation of protein-coding content in sequenced genomes and metagenomic datasets. The research builds on established sequence database search software that employs probabilistic models to increase sensitivity through greater statistical power and ability to better model family complexity. The probabilistic models are called profile hidden Markov models (profile HMMs), and the software is HMMER.
Dr. Wheeler’s group will develop new models that account for frameshifting mutations or errors that obscure the protein-coding nature of sequence, and for splice sites that break genes or domains into distant fragments on the genome. Through a combination of new algorithms and application of existing approaches, these models will be fast enough to use for large-scale annotation, such as in the EMBL European Bioinformatics Institute’s Metagenomics Portal.
(See the press release: here)
I’m proud to be a signatory on a guest column in today’s Missoulian, which highlights the terrific educational atmosphere and excellent research found on the University of Montana campus. Despite trying financial times resulting from an enrollment drop caused by multiple complex factors, this University is home to a great many tremendous educators and researchers.
The Wheeler lab has been awarded competitive pilot project funding through the University of Montana Center for Biomolecular Structure and Dynamics (CBSD). The grant will support early development of methods for reducing false sequence annotation of large genomic DNA datasets due to repetitive sequence and alignment overextension, and will fund two students in our group for the next year. CBSD is supported by a National Institutes of General Medical Science (NIH NIGMS) IdeA program Center of Biomolecular Research Excellence (CoBRE) Phase II grant.
Congratulations to lab member Gilia Patterson, who today was recognized as the University of Montana Outstanding Senior in Genetics and Evolution. Gilia has done great work with me on understanding sources of transposable element mis-classification (manuscript coming soon to a theatre near you), and we’re happy as can be for her!