Lab Interests
The lab interests are diverse, yet there is a common goal: we seek to intertwingle computation with experiment in order to improve our understanding of biology. We intersect with a number of fields, both new and old, including developmental biology, molecular biology, bioinformatics, regulatory genomics, metagenomics, and next-generation sequencing data.
Grant proposals and formal writeups:
- Paper draft: Scaling metagenome sequence assembly with probabilistic de Bruijn graphs
- 2011 / NSF CAREER proposal: "Scaling and Improving de Bruijn graph assembly"
- 2011 / Reappointment
- 2010 / Next-gen course, NIH R25
- 2009 / Web tools for next-gen sequence analysis
- 2007 / Cartwheel
- Neural crest specification in early vertebrate embryogenesis.
- Next-generation sequence analysis.
- Metagenomics.
- Evolutionary developmental biology.
- Animal regulatory genomics.
- Microbial regulatory genomics.
- Evolutionary sequence signatures.
- Software engineering methodologies.
Authors: Jason Pell, Arend Hintze, Rosangela Canino-Koning, Adina Howe, James M. Tiedje, C. Titus Brown.
My first senior author paper!!
Submitted to PNAS on Dec 28th, 2011 (cover letter).
Our submitted / not-yet-rejected grant proposal to work on de Bruijn graph filtering/breakdown approaches for de novo assembly.
"Dear MSU, please do not fire me. I will be good, I promise." A writeup of what I have accomplished and what I hope to accomplish as a professor, and why MSU should keep me around.
(They believed me; I'm hired through 2015.)
Our (accepted) grant proposal to support our summer course on next-gen sequence analysis.
Our (accepted) grant proposal to build an easy-to-use Web interface for next-gen sequence analysis. (USDA NIFA)
A (rejected) grant proposal on the need for easy-to-use Web interfaces for comparative sequence analysis. (NIH R01)
A brief write-up of some of our interests
The neural crest is an important developmental tissue that is specified early on in embryogenesis. We seek to understand the molecular events underlying this specification, using both molecular and embryological techniques, and integrate it with sequence data to produce a gene network model for neural crest specification. (This is our primary experimental focus.)
Advances in sequencing have led to a data tsunami, necessitating advances in algorithms, approaches, and training. We are working on advanced techniques in de Bruijn graph assembly and k-mer-based data set filtering, to apply de novo assembly approaches in metagenomics, mRNAseq, and environmental genomes; one particular emphasis is in adapting de novo assembly to work well within the constraints of the Amazon cloud. We also teach a yearly summer course. (Collaborations with Li lab, Cheng lab, and many others.) This is our primary computational focus.
Most (99% or more) of microbes cannot be cultured in the lab, yet many microbes play important environmental or medical roles. Metagenomics seeks to understand microbial communities by making use of new sequencing technologies to sequence unculturable organisms, yet this data cannot be easily grokked. We are interested in computational ways to analyze and understand metagenomic data. (Collaborations with Schmidt, Tiedje labs.)
The Molgulid ascidians are a fascinating group of invertebrate chordates that have repeatedly and independently lost their larval tails, which is otherwise rare in the ascidians. We seek to understand the genomic modifications that have made this possible, and build a detailed molecular understanding of the tail development network in Molgulids. We are applying modern sequencing techniques to investigate gene expression in M. oculata (tailed), M. occulta (tailed), and hybrids between the two. (Collaboration with Swalla lab at U. Washington, Seattle.)
See also my poster and Elijah's poster from the International Tunicate Meeting in 2011.
Much of early development is "hard wired" in the genome's regulatory elements. Finding and analyzing regulatory elements in animal genomes can be very difficult, given the large size and complexity of these genomes. We are building tools to help detect, visualize and analyze regulatory elements.
Gene regulation is an important part of microbial physiology, yet we still know relatively little about finding and studying regulatory elements computationally in microbes. The smaller size of microbial genomes makes locating transcription factor binding sites easier, but validation still requires difficult experiments. We are particularly interested in techniques for testing the internal consistency of binding site predictions.
As genomes evolve, different selection pressures are brought to bear upon the various functional elements. These functional elements can often be recognized computationally from the signature left by evolution. We are interested in using such signatures to computationally find novel genes and regulatory elements.
A critical component of modern biologiy is digesting and integrating data from multiple sources, both local (e.g. lab data, collaborator data) and remote (NCBI, ENSEMBL, UCSC, other genome databases). This research depends on extensive re-use and maintenance of old software tools as well as development of new software tools, a traditional challenge of software engineering.