Jackson Laboratory

The Dumont Lab

Principal Investigator: Beth Dumont, Ph.D.

The Jackson Laboratory
Bar Harbor, ME

Connect with me:

Researching the mechanisms that generate genetic diversity through the lens of evolution

Our Research Focus

The broad objective of my research program is to understand the causes and consequences of variation in the cellular mechanisms that govern DNA inheritance: genetic recombination, chromosome segregation, and de novo mutation. To date, my work has combined wet-bench and computational approaches in multiple mammalian model systems to investigate variation in two recombination mechanisms, crossing-over and gene conversion. Over the next several years, my research group will work at the leading edge of genomics, evolutionary genetics, and cytogenetics to advance our understanding of recombination rate variation from diverse biological perspectives.

Full Scientific Report

View all research positions

Open Positions

Job	Job Title	Location	Description

Lab Staff

Uma Arora

PhD Student

Investigating the composition and diversity of centromeric sequence amongst Mus musculus subspecies and autosomes vs sex chromosomes to understand their significance in evolution.
Laura Blanco-Berdugo, MS

Research Assistant II

Interested in genetic diversity and evolution of wild and wild-derived mice
Beth Dumont, Ph.D.

Assistant Professor
Brett Haines, B.S.

Research Assistant
Raman Akinyanju Lawal, Ph.D.

Postdoctoral Associate

Unraveling the patterns of genetic mechanisms that give rise to genetic diversity in house mouse populations.
Glenn Smallidge

Research Administrative Assistant II

Provide Research Administrative Support for several faculty members.

Selected Publications

Highlighted Abstract

Knowledge of the rate and pattern of new mutation is critical to the understanding of human disease and evolution. We used extensive autozygosity in a genealogically well-defined population of Hutterites to estimate the human sequence mutation rate over multiple generations. We sequenced whole genomes from 5 parent-offspring trios and identified 44 segments of autozygosity. Using the number of meioses separating each pair of autozygous alleles and the 72 validated heterozygous single-nucleotide variants (SNVs) from 512 Mb of autozygous DNA, we obtained an SNV mutation rate of 1.20 × 10(-8) (95% confidence interval 0.89-1.43 × 10(-8)) mutations per base pair per generation. The mutation rate for bases within CpG dinucleotides (9.72 × 10(-8)) was 9.5-fold that of non-CpG bases, and there was strong evidence (P = 2.67 × 10(-4)) for a paternal bias in the origin of new mutations (85% paternal). We observed a non-uniform distribution of heterozygous SNVs (both newly identified and known) in the autozygous segments (P = 0.001), which is suggestive of mutational hotspots or sites of long-range gene conversion.

View full list of publications

Search MagazineApril 01, 2020
Cancer: Does it run in the family?
Helping clinicians take better family histories improves patient cancer risk assessments.
Press ReleaseMarch 17, 2020
NSF CAREER award to Beth Dumont of JAX
Prestigious five-year grant funds evolutionary genomics research, educational outreach.
- Genetic Tools
- Genetics and Genomics
Press ReleaseMarch 10, 2020
Sheng Li named an AACR NextGen Star
Jackson Laboratory (JAX) Assistant Professor Sheng Li, Ph.D., was chosen as a 2020 NextGen Star by the American Association for Cancer Research (AACR). She is one of 12 early-career cancer researchers recognized for their outstanding work and future potential.
Research HighlightMarch 03, 2020
Unfolding the 3D genome
Three-dimensional genomic compartments and sub-compartments help regulate gene expression across the genome. As more data comes out about 3D genomic structures, there is an increasing need to efficiently identify and characterize sub-compartments and their roles in genome function. Sheng Li and her team developed a new computational tool, SCI, that outperforms previously developed algorithms for this purpose.

Research HighlightMarch 18, 2020
Raising the bar for PDX model cancer research
The results of a new PDXNet consortium study provide a key validation toward translating xenograft findings into clinical treatments for cancer patients.
Press ReleaseMarch 11, 2020
The gene lexicologist
ISCB honors JAX Professor Judith Blake for outstanding contributions to biology
- Genetic Tools
- Computational Biology
Blog PostMarch 04, 2020
Building in silico research models to accelerate discovery
Machine learning and deep learning in particular have a growing influence on everything from how we shop to how we drive—or are driven by self-driving cars. Anshul Kundaje, Ph.D., assistant professor of genetics and computer science at Stanford University, is using similar tools to study large-scale computational regulatory genomics.
Research HighlightFebruary 24, 2020
Gene silencers and their vital roles in development
New research shows that silencers modify 3D chromatin organizations to suppress the expression of certain genes at certain time points during development. Disruption of the process can lead to developmental disorders and has also been implicated in certain cancers.
- Tumor suppressor genes
- Genetics and Genomics