Alan P Boyle
University of Michigan, MI·Genetics
Most of the human genome is not genes but other DNA. This includes over a million mobile elements, DNA segments that have copied themselves around the genome over evolutionary time.
- Fields
Genetics
Computer Science
Biology
- Topics
mobile element insertions
transposable elements
chromatin looping
- Grants
- 2 known grants, through May 2027
What they work on
- Quantify how transposable element activity changes binding of CTCF, a protein that anchors DNA loops, across a population sample of 51 well-studied individuals using computational methods.
- Map fixed and variable LTR13 mobile-element insertions in the CEU reference population and test how they change CTCF binding, chromatin looping and gene regulation between individuals.
- Directly map DNA loops anchored at HERVK/LTR13 elements by combining enrichment capture with chromatin conformation capture read by Oxford Nanopore long-read sequencing.
- Build a reference atlas of cell states from single-cell transcriptomic and epigenomic data in healthy people, and identify quantitative cell-state shifts caused by genetic variation.
- Develop models that predict how combinations of germline variants shift cellular state, integrating single-cell data, chromatin structure and functional data to support the IGVF consortium.
More about the research
Small differences in this DNA between people can change when and where genes are switched on. These differences shape traits and disease risk. A central challenge in genomic medicine is predicting what a given DNA difference actually does inside a cell. The lab's two projects approach this from two directions. One looks at how mobile elements change the folding of DNA. The other builds computer models that predict how combinations of genetic variants shift the state of individual cells.
Why it matters
Many disease-linked DNA differences sit outside genes, and their effects are hard to interpret. Better maps of variable mobile elements could help explain how people differ in gene regulation and disease risk. Models that predict how combined variants shift cell states could help doctors and geneticists interpret a patient's genome. Over time, this could support genomic medicine by linking genotype to the cellular changes that may underlie disease.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Harriet Dashnow
University of Colorado Denver/Anschutz Medical Campus, CO·Genetics·Early-career
Build a public, population-scale catalog of short tandem repeat variation grouped by ancestry, emphasizing diverse and underserved populations, so disease-causing repeat expansions can be prioritized.
Scott Devine
University of Maryland, Baltimore, MD·Genetics
Build a comprehensive resource of full-length, human-specific LINE-1 (FL-L1Hs) source elements, the retrotransposon copies able to produce new insertions, for studying L1 mobilization in human tissues and tumors.
Susan Wessler
University of California-Riverside, CA·Genetics
Map the full range of structural genomic variation, including new insertions, copy number changes, presence/absence variants and inversions, created by the Ping/mPing mobile DNA burst in three rice recombinant inbred populations, using long-read DNA sequencing.
The school
University of Michigan: 124 labs on PI Pages, $2.1B a year on research, 963 research doctorates a year.
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