About
Learn About Us
The Efficiency of mRNA Biogenesis
We aim to understand how RNAs are regulated through the lifecycle of an RNA molecule. To do so, we develop and apply high-throughput approaches to study the kinetics, fidelity, and coupling of transcriptional and RNA processing mechanisms.
Our lab combines experimental & computational genomic tools to probe steps of RNA maturation. We are always looking for enthusastic researchers to join us!
Functional Genomics
genetics, genomics, molecular & cellular biology
Quantitative Analyses
bioinformatics, mathematical modeling, machine learning
Research
Brief Overview of our Research
Kinetics of Transcription & mRNA Processing
The mechanisms of enzymes are encoded in the kinetics of substrate turnover. We postulate that the mechanisms of transcriptome dynamics are similarly encoded in the aggregate kinetics of mRNA biogenesis and maturation rather than steady-state transcriptome profiles. Thus, we directly study the rates at which transcriptional and mRNA processing steps occur, with the central hypothesis is that the temporal progression of RNA maturation mechanisms encodes the molecular underpinnings of developmental trajectories, mis-regulation of disease pathogenesis, and rapid cellular responses to external stimuli.
However, measuring the timing of crucial mRNA processing steps across the genome remains challenging. Thus, a primary focus of our group is to first to develop genomics methods to measure the kinetics of transcription, mRNA splicing, and 3’ end cleavage at high resolution by integrating nascent RNA sequencing across molecular time with statistical modeling and machine learning techniques. We are now applying our novel approaches to relevant mammalian systems to understand the trajectories of mRNA isoform expression.
Fidelity of mRNA Splicing
RNA processing likely involves a critical balance between speed and accuracy – faster processing is likely accompanied by an increase in errors that lead to nonproductive transcripts. However, it is commonly believed that the spliceosome is a high-fidelity deterministic enzyme that rarely makes mistakes. We and others have begun to identify extensive non-canonical splicing that might be the result of stochastic splicing interactions. We have developed computational tools to analyze splicing intermediates in nascent RNA that are informative about splicing fidelity. Work is on-going to understand the regulatory factors and interactions that underlie nuclear quality control mechanisms and how certain RNA molecules evade such checkpoints.
Understanding the molecular basis for RNA processing infidelity is particularly germane to contemporary efforts to redirect inaccurate mRNA splicing in a therapeutic context. We are deploying our computational analyses of nascent RNA to identify splice sites and exons that are amenable to therapeutic targeting and testing the efficacy of such predictions.
Coupling of Co-Transcriptional Mechanisms
Despite an increasing appreciation that mRNA processing mechanisms do not act independently, we do not yet understand how they integrate to control steady-state or transient gene expression levels. Thus, a key open question in functional genomics remains: How do the dynamics of individual molecular processes combine to influence the cellular transcriptome?
The majority of mammalian mRNA isoform diversity is driven by alternative 5’ or 3’ untranslated regions (UTRs), rather than alternative splicing of coding exons. Since exons at the start or end of transcripts are challenging to identify, we first developed computational approaches to systematically identify and quantify terminal exons from short or long-read sequencing data based on their isoform-specific usage. Using these tools, we observed a coordinated relationship between transcription start and end sites that is dictated by the genomic order of alternative sites. We call this new regulatory phenomenon the "Positional Initiation-Termination Axis" (PITA) and show that this coupling is governed by variable rates of RNAPII elongation across a gene. Ongoing work is focused on mechanistic details of PITA and further connections to splice site choice that ultimately determine full isoform composition.
Team
Meet the Group
Athma Pai
Principal Investigator
Ann Latino
Administrative Coordinator
Ezequiel Calvo-Roitberg
Graduate Student
Kelly Cochran
Postdoctoral Researcherjoint with Schärfen lab
Nida Javeed
Research Associate
Eva Jazbec
Graduate Studentjoint with Sontheimer lab
Eraj Khokhar
Postdoctoral Researcher
Marina Krykbaeva
Postdoctoral Researcher
Jesse Lehman
Graduate Student
Ye Liu
Postdoctoral Researcher
Joseph Paquette
Graduate Student
Valeria Sanabria
Graduate StudentPublications
Read Our Publications
- Selected
- Coupling
- Fidelity
- Kinetics
- Collaborative
- All Papers
Software
Computational Resources
We often develop new computational approaches or pipelines and make them freely available to the community. NOTE: we are not software developers and most of these code repositories have not been actively maintained since publication.
Photos
Life in Lab and Beyond
Contact
Let's Connect
Our Address
Albert Sherman Center
368 Plantation Street, AS5-2057
Worcester, MA 01605
Email Address
info@thepailab.org
Locations:
Wet Lab: ASC5-2003/2004
Dry Lab: ASC5-2053/2055
AAP Office: ASC5-2057